Ebook Aftersales service of engineering industrial assets: A reference framework for warranty management

Ebook Aftersales service of engineering industrial assets: A reference framework for warranty management explores the practical implementation of an advanced aftersales management framework devoted to warranty management. The framework is intended for companies producing either standardized or customized products and such a management tool will facilitate organizational improvement and support innovative decision making processes for... Đề tài Hoàn thiện công tác quản trị nhân sự tại Công ty TNHH Mộc Khải Tuyên được nghiên cứu nhằm giúp công ty TNHH Mộc Khải Tuyên làm rõ được thực trạng công tác quản trị nhân sự trong công ty như thế nào từ đó đề ra các giải pháp giúp công ty hoàn thiện công tác quản trị nhân sự tốt hơn trong thời gian tới.

Introduction

In today's complex and globalized market, enterprises encounter numerous challenges related to product management and reliability The high competitiveness and dynamic nature of the business environment require companies to address diverse issues, some of which may not yet be on executives' radar This research focuses on after-sales management and its potential to enhance the reliability of industrial assets, ultimately boosting client satisfaction and achieving financial goals Understanding the significance of relevant keywords is essential for defining these challenges effectively.

A "reference framework" serves as a conceptual model that regulates or contrasts specific subjects, providing a foundational structure for comparison and measurement In this research, the term is utilized to address and guide complex issues across various knowledge areas through descriptive or generic approximations.

After-sales management encompasses the organizational and managerial activities that set objectives, strategies, and responsibilities for after-sales services Its goal is to implement effective planning for technical assistance, resource allocation, and supervision, ensuring that economic factors are integrated into the organization's overall accounting The after-sales concept refers to the duration in which the seller or manufacturer provides the buyer with support, maintenance, or repairs for the purchased product.

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A complex industrial asset refers to valuable resources and rights owned by a business or individual, reflecting their accountability It encompasses material assets linked to the industry that possess a degree of technical complexity, necessitating specialized control and management, such as automobiles, aeronautical components, automation systems, and reactors.

• Warranty: A temporary agreement of the manufacturer or retailer, by which it is obliged to repair with no charge any sold item in case of a breakdown.

This research focuses on the launch of technologically complex products and services that necessitate post-sale assistance, ensuring effective after-sales management through organized resource allocation It proposes a set of generic guidelines to enhance teamwork, facilitate internal and external communication, uphold business ethics, and promote human resources and corporate social responsibility.

Objectives of the Book

The primary aim of this research is to establish a management framework for after-sales service that aligns with the company's objectives, treating it as an integral part of the organization rather than a separate cost center This approach emphasizes the importance of viewing the company as a holistic system, where specialized departments collaborate to achieve shared goals To further this aim, the main objective can be broken down into several secondary objectives.

1 Analyze the state-of-the-art regarding management and warranty of the after- sales service (Part II).

2 Identify the concepts and developed methodologies that come into effect for other areas of management such as maintenance, and to apply them to cases of warranty assistance (Part III).

3 Develop the implementation of these methodologies regarding the after-sales service (Part IV).

4 Justify the importance of the research with future extensions or possible lines of research in this area (Part V).

4 1 Researching the After-sales Services and Warranty Management

The research establishes a framework to support warranty program management, emphasizing actions that enhance product reliability and the relationship between manufacturers and users By re-engineering management processes and optimizing after-sales service organization, the framework facilitates improvements in product design and manufacturing, thereby boosting quality and reliability through better information flow regarding defects and their causes To make the broad research objectives more manageable, they are divided into specific research questions, with their answers collectively contributing to a comprehensive understanding of the topic A well-structured after-sales approach can significantly increase a business's economic benefits, not only through secondary product sales like spare parts and maintenance contracts but also by identifying and resolving underlying issues that lead to user problems.

To enhance comprehension of key issues in this field, the research will first focus on the methodologies currently employed in maintenance, process improvement, and their associated capabilities.

Various studies, models, and approximations have significantly contributed to the identification, analysis, elimination, and prevention of issues arising from failures in industrial assets By leveraging advanced analytical techniques and predictive modeling, these approaches enable organizations to detect potential failures early, allowing for timely interventions Furthermore, the integration of data-driven insights facilitates a deeper understanding of failure mechanisms, leading to more effective maintenance strategies and reduced downtime Ultimately, these methodologies enhance operational efficiency and ensure the longevity of industrial assets, driving better performance and cost savings.

Leveraging established methodologies from other sectors can enhance organizational maturity in after-sales service management This approach prompts a deeper exploration of the research's second question.

• 2nd Question: What systems are proposed to provide after-sales service to make the most of the advantages of the successfully applied methodologies in other areas?

Effective decision-making in after-sales service is crucial, as it involves selecting the appropriate policies and ensuring the right follow-up procedures are in place Implementing a systematic approach is essential to guarantee that decisions are grounded in factual data.

OPERATIONS WITH THE CLIENT Warranty Definition Warranty Purchasing Service Contract

FINANCIAL MANAGEMENT Payment Accounting Budget

Operational Report Suppliers / Repair Performance / Quality REPAIR MANAGEMENT

Fig 1.1 General scheme of warranty management

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d correct follow-up procedure is being properly applied With this in mind, the third question of the research is:

• 3rd Question: What should the after-sales service be like in order to be efficient and advantageous from a business point of view?

The book describes a cyclical procedure of improvement, selecting a determined management policy, and carrying out a follow-up check of its performance.

To determine the most suitable policy, it is essential to establish a framework for measuring its impact on company decisions both before and after implementation This prompts the next inquiry.

• 4th Question: How should technical and financial performance in the after-sales service be assessed and controlled so as to allow improvement during the management of its procedure?

To effectively assess the performance of technical assistance, it is essential to access relevant service information, which poses a complex challenge due to the after-sales impact of industrial assets across various business areas Additionally, commercial data on asset behavior among different user types is often limited or highly diverse, prompting the need for further investigation into this issue.

• 5th Question: What information should be relevant to make decisions regarding the after-sales service and what are the future researches that arise from this line?

Figure 1.2 shows how the suggested questions relate to each part of the research.

This book addresses the critical issue of selecting an effective policy for a warranty assistance program and monitoring its performance to enhance both profitability and the company's reputation The subsequent section outlines the content of the relevant chapters and summarizes the book's structure.

Rational of the Methodology Followed

Origins and Background (Part II)

Chapter 2 outlines a realistic scenario that highlights the complexities of supply chains, focusing on the internal operations of a typical manufacturing company and its interactions with clients and suppliers This context sets the stage for discussing warranty-related issues, providing a clear and concise understanding of the challenges faced in managing these relationships.

Fig 1.2 Relation between the research questions and the chapters

1.3 Rational of the Methodology Followed 7

This research begins by emphasizing the various types of warranties that are appropriate for different product categories, such as consumer goods, commercial products, and industrial items In this context, the study focuses on after-sales management within a company that offers services over a defined period and follows a specific delivery schedule The analysis specifically targets personalized or customized products, where the warranty terms can be negotiated with the client.

Chapter 3: State-of-the-Art examines relevant studies on modern warranty management, highlighting innovations, functions, and objectives proposed by various authors This analysis reveals the characteristics and properties of diverse scenarios, establishing a comprehensive taxonomy for applying effective management strategies in this field.

Methodology and Resolution Proposal (Part III)

Chapter 4 focuses on various maintenance management models, highlighting the innovations introduced by different authors It analyzes the essential characteristics of an effective modern maintenance management model, which include a clear implementation methodology, necessary supporting tools, and a preference for cyclic processes Based on these attributes and the key elements from each model, a new maintenance management model is proposed, aligned with the ISO 9001:2008 standard.

Chapter 5 presents a comprehensive reference framework for managing warranty assistance, utilizing established engineering techniques tailored for similar processes This framework integrates existing models into four sequential stages, highlighting the essential role of various techniques in enhancing warranty management efficiency.

These four stages will contemplate effectiveness, efficiency, evaluation, as well as the constant enhancement of the management of after-sales service.

In Chapter 6, we will evaluate the initial scenario discussed in Chapter 2 against the criteria established in Chapter 5 This comparative analysis will also provide a concise overview of the quality aspects essential for enhancing the overall framework.

Effective after-sales management, along with various contemporary business practices, plays a crucial role in quantifying and assessing a company's maturity level.

Development of the Proposed Stages (Part IV)

Chapter 7 focuses on the effectiveness of aligning local after-sales objectives with the overall business goals through the Balanced Scorecard framework This model aims to prevent the formation of a compartmentalized organization, where independent decision-making could hinder future development and harm the company's image to customers.

This chapter explores the Analytic Hierarchy Process (AHP) as an effective decision-making tool that aligns after-sales actions with business objectives in warranty management It concludes with an examination of root failure analysis, highlighting its importance in improving decision-making processes.

Chapter 8 focuses on enhancing efficiency in after-sales service to minimize losses and unnecessary expenses It defines efficiency as providing the same level of service at a reduced cost Key components such as Integrated Logistic Support, repair levels, and duty frequencies are outlined The chapter also includes a concise Cost, Risk, and Benefits Analysis tailored for after-sales service, demonstrating how project management tools can effectively streamline and manage technical support for customers during the warranty period.

Chapter 9 focuses on the assessment and control of industrial assets, emphasizing the importance of considering various restrictions and conditions in equipment design It highlights the need to account for potential failure modes in components or subsystems from the initial design phase, influenced by factors such as operational methods, environmental conditions, and timing of failures The RAMS Analysis provides a valuable evaluation of equipment performance under severe conditions, particularly in complex systems within sectors like aerospace, defense, and self-propulsion The acronym RAMS encapsulates key concepts typically expressed in probabilistic terms.

– Reliability is the capacity of a system to carry out the functions that are expected from it, under established conditions and during a specified period of time.

– Availability is the degree to which a system can be used during a determined period of time It is usually expressed as a time ratio.

Maintainability refers to the design and installation features of an element that require it to be restored or replaced after a specified duration, following established maintenance procedures.

– Safety is the condition of being protected against failures, errors, damage, or any other incident that can be considered undesired.

This chapter also covers the Life Cycle Cost of the physical asset, which is assessed by identifying the product’s functions at each life stage, calculating the associated costs, and applying relevant expenses throughout its entire life cycle.

Chapter 10 explores the role of ICTs in enhancing physical asset management and warranty assistance, emphasizing their qualitative impact within a structured framework and their integration with other stages of customer support It highlights how effective customer relationship management can inform decision-making for after-sales services, such as strategic replacement procurement and customer classification, while adhering to contractual and legal standards governing client interactions in warranty contexts The chapter also connects these after-sales management practices to current market realities and concludes with an overview of the Six Sigma Method, detailing its components and its synergy with other methodologies and tools.

Extensions to the Proposed Reference

Chapter 11 highlights the significance of technical assistance and intellectual capital in after-sales services, which encompass various disciplines such as management, human resources, and environmental management This department plays a crucial role in addressing client needs and enhancing company profits Intellectual capital serves as a vital tool for improving maintenance, emphasizing the importance of technical knowledge, adaptability, creativity, teamwork, and decision-making abilities among maintenance staff Recognizing the knowledge of maintenance personnel as a strategic asset can provide a competitive advantage, making it essential to evaluate these factors for effective contribution to the company's valuation and future strategies.

• Chapter 12: Maintainability in the after-sales management This chapter con- tains a procedure that obtains the maintainability indexes for industrial devices.

This analysis is essential for comparing and selecting systems to enhance device design based on technical assistance program requirements, improve after-sales services in specific industrial environments, and prevent maintainability issues due to temporary relocations It defines key characteristics and outlines the various levels of technical assistance, leading to the evaluation of applicable indexes for any industrial asset or user during both preparation and operational phases Accurate measurements require identifying the device's life cycle stage and the client's specific usage conditions at that time.

Chapter 13 focuses on the significance of integrating assistance services with the sale of industrial products in mature markets, highlighting the added value of combining tangible products with intangible services to meet specific customer needs Key services such as spare parts supply, technical support, repairs, installations, reconditioning, inspections, and maintenance not only enhance customer satisfaction but also provide a stable income source, proving more resilient to economic fluctuations than traditional sales The chapter presents a dynamic model designed to quantitatively analyze the causal relationships and impacts of new after-sales policies aimed at improving customer service Additionally, it introduces a novel approach to after-sales service at the end of a product's life cycle, utilizing Bayesian nets theory to develop an optimal plan for dismantling complex industrial systems and facilitating recycling.

The Case Studies

The book features a collection of case studies that provide practical insights related to each chapter, enhancing understanding of key concepts While the introductory and concluding chapters, as well as those discussing state-of-the-art and methodology, are exceptions, the majority of the chapters include exercises or examples designed to facilitate reader comprehension of the theoretical content.

Case studies are commonly employed in engineering and various research fields to enhance comprehension of diverse topics and theoretical advancements.

The abundance of information available regarding case descriptions can either oversimplify or overly complicate analysis Therefore, the goal is to synthesize case studies with practical applications that clearly demonstrate how specific methodologies are implemented in after-sales service to reduce costs This approach aims to enhance decision-making processes and improve the business's market image Emphasis is placed on diverse study scenarios, as illustrated in Table 1.1, each examining unique aspects of after-sales warranty management for industrial assets under warranty.

Current Issues in Warranty Management

Background

Effective warranty management relies on the collection of accurate data and the seamless exchange of information across various system modules This article proposes a modular approach to warranty management, highlighting the interactions between warranty processes and other disciplines as discussed in the literature Notably, three key interactions warrant attention for a comprehensive understanding of warranty management systems.

1 Warranty and Maintenance: In many cases, the warranty period is the time when the manufacturer still has a strong control over its product and its behavior Additionally, the expected warranty costs normally depend, not only on warranty requirements, but also on the associated maintenance schedule of the product [4].

2 Warranty and Outsourcing: The warranty service or, in general, the after-sales department of a company, is usually one of the most susceptible to be out- sourced due to its low risk and also to the fact that, among other features, outsourcing provides legal insurance for such assistance services [5].

3 Warranty and Quality: The improvement of the reliability and quality of the product not only has an advantageous and favorable impact in front of the client, but also this improvement highly reduces the expected warranty cost [6].

In the vehicle industry, a low ratio of customer claims does not necessarily indicate high quality, as some companies may redirect claims to suppliers instead of addressing them This practice can distort the perception of product quality The accompanying figure illustrates the percentage of revenue allocated to warranties in relation to vehicle sales.

4 Warranty and Cost Analysis: In reference to costs estimations (see Fig 2.2), and apart from warranty issues, there are nowadays several methods to accurately estimate the final cost of a specific acquisition contract In our case study, the method applied in a simplified way is denominated ‘‘Estimate at Completion’’

EAC, or Estimate at Completion, is a vital project management technique utilized for effective cost control throughout a project's lifecycle It enables project managers to predict the total project cost at completion by integrating key metrics related to the project's scope, delivery schedule, and associated costs into a cohesive system Additionally, warranty costs can be factored into the overall project analysis, allowing for accurate estimations of service costs incurred at the end of the contractual obligations.

18 2 An Initial Case Study Understanding Warranty Management Issues

Case Study Scenario

The case study focuses on a global metal industry manufacturer that designs, manufactures, and purchases a diverse range of industrial vehicles, including machinery for forestry, hydraulic excavators, and track loaders, along with spare parts Customization of these machines has become increasingly common, necessitating the company to deliver a specified number of tailored vehicles on a set schedule The contract includes warranty assistance for the fleet's vehicles, commencing upon delivery To ensure satisfactory after-sales service, certain conditions must be met.

1 Teams formed by properly trained personnel.

2 Tools for maintenance/warranty tasks.

3 Materials and spare parts to carry out the repairs.

Fig 2.1 Ratios of warranty claims from 2003 to 2013

EAC = Incurred To Date + Estimate To Completion

Fig 2.2 EAC formula (adapted from [7])

The initial two conditions have been met, while the third condition is satisfied by sourcing the necessary materials for warranty operations from the same warehouse as the assembly line This approach allows for two options to recover the materials effectively.

• When the piece is repairable, a spare part is taken from the warehouse, which is later returned after the disassembly of the product being repaired.

• When the piece is not repairable, a spare part is also taken from the warehouse, but it must be restored by the purchase of another.

The manufacturing stock enables the provision of materials for warranty assistance without jeopardizing assembly line needs However, challenges arise when manufacturing and warranty services share the same warehouse, leading to potential conflicts when production is advanced while numerous vehicles require warranty support Decisions must then prioritize one activity over the other Additionally, the study utilizes historical data on costs and faulty items during the distribution of deliverables A hierarchical classification tree is employed to categorize faulty items based on functionality, ensuring detailed procurement insights The scenario and delivery schedule are illustrated in Table 2.1, and the case study will consider specific hypotheses.

• Every vehicle has the same reliability (they have the same failure probability).

• The warranty cost is constant with the time.

• The warranty time does not stop at any moment.

The Estimated Average Cost (EAC) for warranty is influenced by company policy and typically calculated as a percentage of the total project cost In our case study, the overall expenses, including manufacturing and indirect costs for each vehicle, total approximately €375,000.00, with a specific percentage allocated for warranty coverage.

2 % of the budget for total costs That yields around 2,625,000.00 € for the attendance of warranties during the whole project.

Analysis, Development, and Results of the Case Study

The previous chapter's literature review presents numerous case studies focused on data analysis derived from warranty assistance, encompassing both qualitative and quantitative data This analysis utilizes real data, providing extensive insights into the subject Comprehensive examinations of this topic can be found in references [8] and [9].

2.3.1 Costs Analysis of the Warranty Assistance

The study is conducted after the company has delivered 150 vehicles, with 105 of them currently under warranty Preliminary data is presented in Table 2.2, which includes a sample of vehicles under warranty based on the established delivery schedule Certain figures have been rounded for ease of use throughout the study.

Table 2.2 provides a sample from the full delivery schedule, indicating that the warranty expiration date for the initial vehicles is March 2010, with a critical moment occurring in September 2013, as illustrated in Fig 2.3.

In April 2014, the fleet of 315 vehicles will reach a peak of 115 units under warranty, highlighting the urgency of delivering the final vehicles by April 2015 This critical period will require our maintenance and warranty technicians to manage a high volume of vehicles, necessitating a significant supply of spare parts Simultaneously, assembly line operators will need components for the production of the last units While the shared warehouse can support manufacturing needs, it lacks surplus inventory for after-sales requirements Therefore, the procurement of spare parts must prioritize the significance of the materials, repair times, and the duration needed for purchasing replacements The criticality of each component in the classification tree will fluctuate over time, impacting our operational efficiency.

Every piece will be considered much more critical as the end of the manufacturing process gets closer Therefore, and taking also into account a costs analysis, it is

Table 2.1 Data of the described scenario Date Accumulated amount of vehicles

Total amount of customized vehicles to be delivered: 350 units Warranty period for each vehicle: 2 years

Warranty expiration for last vehicle: March 2017 Time point of the case study (t 1 ): April 2011 (150 unit already delivered)

2.3 Analysis, Development, and Results of the Case Study 21

3a67e368 0a4d3d50 cf8d5 f476 8201 e328 cbbba50 c741 ebd4f6 b2e1 0316e d218 e1d2 918 necessary to bear the investment of a minimum strategical stock in mind in order not to leave warranty claims unattended.

Considering the data indicated above, it is possible to carry out a simple costs analysis obtaining some average values Calculation of some values:

Table 2.2 Extract of the delivery schedule Date Accumulated amount of vehicles

Number of delivered vehicles t 1 : V 1 = 150 units Number of warranty claims in t 1 : R 1 = 1,200 warranty claims Warranty incurred cost in t 1 : C 1 = 1,000,000.00 €

EAC for Warranty: EAC w = 2,625,000.00 € Number of vehicles to be delivered: V(t) = (according to delivery schedule)

Evolution of vehicles under warranty

0 50 100 150 200 250 300 350 400 ma r- 0 8 se p -0 8 ma r- 0 9 se p -0 9 ma r- 1 0 se p -1 0 ma r- 1 1 se p -1 1 ma r- 1 2 se p -1 2 ma r- 1 3 se p -1 3 ma r- 14 se p -1 4 ma r- 1 5 se p -1 5 ma r- 1 6 se p -1 6 ma r- 1 7

Am ount of ve hi cl e s

Monthly delivery Cumulative Vehicles under warranty t 1 t 2

Fig 2.3 Warranty evolution graphic, in terms of deliveries

To illustrate the warranty cost evolution, a graphic (Fig 2.5) is provided, depicting the total incurred warranty costs for each vehicle in a conservative manner These costs are accounted for as already incurred upon the delivery of each vehicle, meaning that the accumulated warranty costs remain unchanged after the last vehicle is delivered Future studies may explore various vehicle destinations, where a maximum number of local vehicles may occur at different times throughout their defined lifespan, necessitating the inclusion of costs related to the deployment of warranty teams to various locations.

A comparison of the results with the projected costs in the Estimate at Completion (EAC) yields a graphic representation, as illustrated in Fig 2.5 The EAC consists of two components: the first part, known as Incurred to Date (ITD), and the second part, represented by the continuous gray line, which indicates the Estimate to Completion (ETC).

The analysis reveals that the final cost, approximately €2,335,000, is slightly below the initial project budget of €2,625,000, resulting in a budgetary buffer of around €290,000 This surplus can be allocated for strategic investments in spare parts, equivalent to the warranty coverage for about 43 vehicles or utilized for warranty assistance approximately 15 months prior to the manufacturing process's conclusion Additionally, the estimated total number of warranty claims is projected to be around 2,800.

To ensure optimal client service, it is crucial to procure strategic spare parts separately from the assembly line stock This approach enables independent warranty support without impacting the manufacturing department, thereby safeguarding the project's overall objectives.

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Fig 2.4 Classification tree of components2.3 Analysis, Development, and Results of the Case Study 23

2.3.2 Quantitative Analysis of the Claims

Data has been collected on a wide range of items associated with customer complaints, categorized by functionality and subdivided into procurable components (refer to Fig 2.4: Classification tree of components) A sample of this data is illustrated in Fig 2.6, providing an example for this case study.

Analyzing warranty incidents not only benefits the quality department but also enhances the manufacturing process by identifying components with frequent issues By refining manufacturing techniques and paying closer attention during assembly, companies can minimize complaints about specific items In complex systems like industrial customized vehicles, it's essential to select key components for easier data management, where criteria for selection extend beyond just failure rates to include costs and procurement times Understanding the criticality of each component is vital for production line efficiency and decision-making These factors will be assigned specific weights, aiding managers in making informed choices By applying statistical concepts to transform data into relative frequencies, companies can better evaluate component performance and address failures effectively.

Costs evolution of warranty assistances

- 500.000,00 1.000.000,00 1.500.000,00 2.000.000,00 2.500.000,00 3.000.000,00 ma r- 08 ma r- 09 m ar -1 0 ma r- 11 ma r- 12 m ar -1 3 ma r- 14 ma r- 15 ma r- 16 ma r- 17

Average monthly cost Average cumulative cost Incurred + Pending t 1 t 2

Fig 2.5 EAC versus average cost line

To effectively manage resources, it is crucial to prioritize warranty assistance supplies and maintain the necessary components for the manufacturing process, as illustrated in Table 2.3.

A very interesting reference regarding analysis of data statistics is [10], where data analysis is used for the improvement of TQM The rest of the components are basically not considered because:

• They have been affected by a very small number of failures.

• They have been delivered fast enough and mostly in time.

• There is extra stock in warehouse due to the purchasing of a minimum amount of pieces, greater than the real necessity.

• Or they are not, definitively, under the interest of the project managers’ point of view, due to other reasons.

In summary, by identifying and selecting critical components, we are effectively creating a strategic list of spare parts This preparation ensures that if the company decides to utilize the budgetary buffer for warranty services, the purchasing process can be initiated swiftly, ultimately leading to positive returns for the organization.

Pump Engine Battery Brake Valve Alarm Gear Disjunctor Regulator Lights Intercom Antenna Seats Heater Navigator Horn Steering wheel Cable

Fig 2.6 Number of complaints per component2.3 Analysis, Development, and Results of the Case Study 25

• By reducing the probability of paying penalties due to global delay in the project delivery.

• By improving the confidence of the client due to the completion of contractual terms, such as the warranty assistance.

It is important to note that the failures discussed are classified as warranty incidents, but future research will also consider non-warranty cases Analyzing these events requires examining potential causes, such as inadequate user training, insufficient maintenance information, or customers' familiarity with different product behaviors Regardless of whether the failure is linked to the manufacturer, the company should remain engaged in understanding the underlying reasons.

2.3.3 Spare Parts Management for Warranty Assistance

The logistics of warranty services involve critical considerations, as highlighted in Ref [11] Transitioning from assembly line use to warranty support incurs additional costs, impacting the overall project budget These extra expenses arise from the disparity in pricing between bulk purchasing at the project's outset and the individual acquisition of spare parts for specific incidents during the project's lifespan Consequently, effective management must implement strategies to address and compensate for these increased costs.

To avoid significant increases in total manufacturing costs, it is crucial to understand the difference in values while managing overall warranty expenses.

The Importance of a Warranty Management System

Many manufacturing companies allocate significant portions of their budgets to product and service warranties, yet this investment often goes overlooked Implementing effective warranty management processes is essential for maximizing the value of these warranties and ensuring customer satisfaction.

Fig 3.1 Warranty of a business in a supplier chain

Fig 3.2 Ideal case without any defects

Many executives have yet to finalize their strategies regarding warranty management Typically, companies focus on these processes only when facing substantial liabilities from claims or recalls This oversight leads to missed opportunities for considerable cost savings and enhanced business value through improved product quality and increased customer satisfaction.

Effective warranty management involves strategic and operational decision-making, necessitating a comprehensive understanding of the interactions among engineering, marketing, and post-sale support within manufacturing firms.

Effective warranty management should be viewed as a valuable asset rather than a cost center, as it can significantly enhance business performance To achieve this, organizations must integrate best practices and identify critical decision-making points, which are influenced by their existing service management and warranty management capabilities Implementing targeted actions in these areas can lead to improved business performance and increased value creation.

• Reducing the time for claims handling;

• Reducing costs by introducing more automated processes;

• Reducing customer loss due to poor product quality;

• Improved supplier selection and collaboration, cost sharing and quality programs.

Effective warranty management leads to reduced warranty costs, improved product quality, and increased customer retention It necessitates a focus on not just warranty processes, but also the development of enhanced strategies, the implementation of efficient tools, and the integration of systems, alongside the establishment of robust organizational structures.

Fig 3.3 Warranty interactions (adapted from [3])

3.1 The Importance of a Warranty Management System 35

Literature Review

A comprehensive global perspective is essential, encompassing articles, essays, and significant works from the inception of the subject to the most recent sources Notably, previous studies, such as [4] and [5], contain around 1,500 classified references across various categories, providing detailed documentation Additionally, to explore warranty cost modeling, this research utilized a bibliographical search across multiple electronic databases available online.

• Compendex (Engineering Village)—Elsevier Ingeniería de la Información

• ISI Web of Knowledge—ISI

Up to now, the management of warranty has received very little attention, at least as consumer products are concerned [3] Nevertheless, searching concepts as

Numerous studies have explored the concept of "warranty" and the "warranty management model" from various perspectives, addressing key issues outlined in Table 3.1 in chronological order.

This summary chart outlines key articles pertinent to warranty management research, offering a comprehensive overview of the topic While numerous other articles were identified based on relevant keywords in various journals, they were excluded due to differing scopes and objectives The selection criteria for the included articles were primarily focused on their alignment with the research's goals.

1 The article proposed a warranty cost management model.

2 The article was published in scientific journals.

3 The article presented not only a review or an application, but also a model proposal.

4 The model in the article had preferably a graphical/mathematical representation or a software application.

The chronological summary of warranty cost models highlights significant contributions from various authors over the years In 1976, Amato, Anderson, and Harvey introduced a general warranty modeling framework By 1989, Murthy advanced the field with a usage-dependent warranty costing model In 1993, Mitraq and Patankar integrated a multicriteria approach for warranty cost estimation and production Zhang and Pham, in 1999, focused on a model that accounted for warranty costs, error rates, removal times, and associated risks Wang and Sheu (2001) examined the economic implications of warranty effects on manufacturing quality The same year, Kulkarni, Mitra, and Patankar proposed a time-dependent warranty policy for renewable minimal repairs In 2003, Mondal, Pal, and Manna applied cost estimation techniques to a renewing warranty policy Chukova and Hayakawa (2004) analyzed non-renewing warranties with repair times, while Dimitrov et al explored age-dependent failure models Hayakawa and Chukova (2005) investigated quasi-renewal inter-repair times in warranty cost analysis Wang (2006) considered warranty cost models with imperfect repairs and preventive maintenance, and Wu and Xie analyzed warranty costs for non-repairable service products Finally, Williams (2007) related warranty costs to software reliability, showcasing the evolution of warranty modeling over three decades.

The discussed articles provide a straightforward overview of the current advancements in warranty cost management In addition to these contributions, numerous other papers, books, and essays exist that explore the same topic, offering varied perspectives on the subject Researchers from various fields have examined different facets of warranty management, which are crucial for effective oversight For further insights, refer to [19].

Models and Support Tools for Warranty Cost Management

Effective warranty management requires that decisions regarding warranties be made early in the product life cycle, rather than as an afterthought before launch Common challenges in implementing warranty services include various logistical and operational issues that can arise throughout the process.

• Information systems support often limited.

• Long cycles of time for claims review.

• Excessive number of invalid claims.

• Not to distinguish warranty responsibility.

• Warranty data not used to improve product quality.

• Additional claims due to slow corrective actions in manufacturing, engineering, or product design.

Effective warranty management is crucial for avoiding negative circumstances and ensuring product reliability, as it highlights the connection between warranty and reliability The literature offers valuable insights into identifying essential processes, actions, and tools for managing warranty costs effectively A robust warranty management model can significantly enhance a company's warranty service performance By reengineering management processes and applying an appropriate warranty cost model, organizations can achieve their goals more successfully.

• Improve sales of extended warranties and additional related products (maintenance contract, spare part supply, technical assistance).

• Improve the quality by improving the information flow about product defects and their sources.

• Improve relationships with the customer.

• Reduce expenses related to warranty claims and processing.

• Better management and control over the warranty costs.

• Reduce invalid-related expenses and other warranty costs.

When managing warranties, it is essential to differentiate between the organization of warranties for products that are still in production and those that are already available in the market Effective warranty management relies on the accurate collection of data and the seamless exchange of various types of information between the different modules of the management system.

A Reference Framework for Warranty Management

Introduction

The European Standard UNE 13306 (2001) defines maintenance management as the activities that establish objectives, strategies, and responsibilities, executed through planning, control, supervision, and improvement of organizational methods, including their economic aspects Various authors have developed models and frameworks to enhance maintenance management methods, each with unique strengths and weaknesses This chapter presents a chronological overview of these models, highlighting their applications in warranty management organization The analysis of these models has led to a management proposal aligned with ISO 9001:2008 standards.

Maintenance Management Models

In Chapter 3, various contributions to warranty management were discussed, and similarly, this section focuses on maintenance management, identifying essential processes, actions, stages, tools, methods, and techniques for effective maintenance management These methodologies will form the foundation for developing a management framework tailored to after-sales management The chronological contributions related to maintenance management models are illustrated in Fig 4.1, with selection criteria mirroring those established in Chapter 3.

1 The proposed management model has to be global and not focused on just one phase of management or maintenance tool.

2 The model must not be an automated software or CMMS type.

V González-Prida Díaz and A Crespo Márquez, After-sales Service 55

3 The model must be published in a scientific journal or review.

4 The model proposed must be new and not a revision or application of an existing one.

5 The model preferentially must have a graphic representation.

Each model proposal has its strengths and weaknesses, making it essential to analyze them to leverage their best aspects for practical application This review highlights the chronological contributions of key authors in enhancing maintenance management models Table 4.1 presents a summary of proposed innovations for each model in chronological order Notably, the compilation of models by Ref [15] provides a detailed justification for the various innovations proposed It's important to clarify that these innovations represent the first appearance within a maintenance management model, though they may not necessarily be new concepts in the broader context of maintenance.

Briefly discussed, results presented in Table 4.1 can distinguish that throughout the time, maintenance management models have been acquiring new elements such as:

2 Innovative proposal in technical aspects, for example oriented to maintenance re-engineering.

3 The development of models in a standard language of information exchange with the view to be used in GMAO applications.

4 The quantity and quality of the maintenance information required (operational and financial data) have led to the successive incorporation of quantitative techniques and software tools, mainly to deal with matters of maintenance Fig 4.1 Chronology of maintenance management models

56 4 Learning from Maintenance Management Models

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d management efficiency Later efforts have been developed to introduce new methodologies and instruments to improve the efficiency of maintenance.

5 The software tools have made it possible to continuously improve and evaluate the function of maintenance This is due to the quality and quantity of indicators and developed methods to study the efficiency and effectiveness of their operations.

6 There is a recognized necessity that the area of maintenance be effectively linked to productive assets and to other areas of organization The revolution of

Table 4.1 Innovations on maintenance management models

1990 1 Suggest a complete system of maintenance indicators Pintelon and Van

1992 2 Expose the necessity of a link between maintenance and other organizational functions

3 Highlight the importance of the use of quantitative techniques for management

4 Propose organization by levels to execute maintenance functions

5 Discern the usage of expert systems

1995 7 Propose an analysis of efficiency and effectiveness of maintenance

8 Emphasize the importance of leadership in maintenance management

9 Introduces the concept of Reengineering of maintenance Campbell [6]

1997 10 Suggest the model base don the concept of situational management theory

2000 11 Propose the usage of a great variety of tools and Japanese concepts for the statistical control of maintenance processes, using a module called ‘‘feedback control

2001 12 Orientate their model to automated use, expressing it in the language IDEF ỉ (standard language of model)

2002 13 Discern usage of e-maintenance Tsang [10]

14 Propose a guide to analyze the convenience of subcontracting as an element of entrance to maintenance system

15 Incorporate tacit knowledge as well as explicit and integrates it in an automated database.

16 Values specially the management of knowledge within a maintenance model

2006 17 Suggest the unión of tools QFD and TPM within a maintenance management model

2007 18 Propose that maintenance must focus on the fulfillment of requirements of all interested parties

19 Contributes a model with a methodology of application clearly expressed, orientated to the improvement of operational reliability and the life cycle cost of industrial assets

3a67e368 0a4d3d50 cf8d5 f476 8201 e328 cbbba50 c741 ebd4f6 b2e1 0316e d218 e1d2 918 e-maintenance [16] leads us to a new model of potential management, but also to new demands in the business capabilities.

7 The management model begins to include the evaluation of the products’ life cycle and also the maintenance function evaluation The management tends to integrate the asset strategy with that of maintenance.

Recent years have seen a trend in model development towards creating closed-loop systems that prioritize process and quality, incorporating supporting techniques, methods, and tools to enhance decision-making and drive maximum organizational efficiency.

Process-Oriented Models Versus Declarative Models

Section 4.2 outlines key management models introduced in recent years, categorizing them into two main types: declarative models and process-oriented models, as illustrated in Table 4.2.

Declarative management models outline the components of a management system but often lack clarity in the intercommunication between them, making it difficult to perceive aspects related to functionality, interrelations, or synchronization While some declarative models are comprehensive in their coverage of maintenance aspects, process-oriented models excel in clearly depicting the flow of information between components and often represent a closed circuit sequence These process-oriented models tend to be more practical for organizational application compared to declarative models Understanding the strengths and weaknesses of each model is essential for effectively determining the most suitable approach for specific situations and conditions.

Maintenance Management Models Comparative Analysis

To enhance the precision of model comparisons, it is beneficial to develop a verification checklist that encapsulates the key elements commonly observed in various management models over time The initial set of verification criteria can be derived from the ISO 9001:2008 standard.

The international standard for quality management systems serves as a generic guide for processes, including maintenance, that must meet specific requirements Notably, the number of quality elements outlined in Table 4.3 is fewer than those originally specified in the standard, as some components have been consolidated based on their significance to maintenance, which is viewed as a vital aspect of an organization's overall quality system Additionally, some models focus solely on listing the elements necessary for a maintenance management system.

Table 4.2 Classification of declarative and process-oriented models [15]

Declarative models Process-oriented models Pintelon and Van

Table 4.3 Verification list for the analysis of management models Typical elements of a quality system Supporting techniques to maintenance management Quality management system

1 Process-based system input/output

2 Sequence and interaction of processes

3 Description of elements of each process

4 Generation of documents and/or registers Responsibility management

5 Link with policies or strategic objectives of the organization

8 Clear definition of responsibilities and authorities

10 Proposed tools for its execution Resources management

11 Resources management (people, material, infrastructure)

12 Purchase control Measurement, analysis and improvement

13 Audits, internal studies on customer satisfaction, information analysis, corrective and preventive actions, etc.

1 Study techniques for economical and financial aspects of maintenance

3 Specific techniques for human resources management

4 Application of operation research of or administrative sciences

8 Maintenance policies: FBM, UBM, CBM, OBM, DOM

4.4 Maintenance Management Models Comparative Analysis 59

Most maintenance management systems focus solely on their internal dynamics, but there's a lack of clear methods for implementing and operating such systems, highlighting a need for more defined approaches in this area.

Declarative models lack a process-oriented input/output focus and do not provide a clear methodology for application Additionally, these models typically do not address advanced quantitative techniques in maintenance.

• In all of the models, documents and registers are generated as entries for the decision-making process.

• All of the models define the objectives of the function of maintenance; however, not all of them link these objectives with the strategic objectives of the business.

• The majority of the models do not make a clear reference to principles of responsibility, authority, and good communication.

• Approximately half of the models incorporate the use of support techniques of operative research and management methodologies.

• The techniques TPM and RCM are the most mentioned maintenance methodologies.

• In general, TPM and RCM tend to appear together in the management models.

• CMMS is mentioned as an indispensable tool in the majority of the models.

The most recent models include other functions of ICTs in the improvement of maintenance management (e-maintenance and expert systems) These tools also permit us new necessities of organization.

• The majority of the models are not linked to the functioning systems of technical support tools.

• Very few models include the use of simulation, reliability theory, and/or expert systems.

• Almost a third part of the models does not mention inventory management and purchase control techniques.

• The majority of models refer to economic aspects and financial analysis of maintenance function.

• Curiously in previous models, one can see a greater emphasis in aspects related to management of human resources.

Recent models in human resources primarily focus on security and hygiene, suggesting that contemporary organizations have sufficiently addressed salary-related issues.

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d personal satisfaction, training, and other basic aspects of traditional human resources.

5 About measurement, analysis and improvement:

Most models incorporate various stages of maintenance, including evaluation, analysis, and improvement Notably, just over half of these models explicitly reference the concept of "continuous improvement," although there is a growing trend towards its inclusion.

6 About the methodology and functioning of the model:

• A very important attribute of some of the models is the inclusion of an application of methodology, which stimulates continuous improvement.

Maintenance Management Model Based

The analysis identifies recurring concepts related to tools, elements, and activities across various models, which are categorized into planning, support processes, maintenance, control, and improvement execution These categories align with the ISO 9001:2008 quality management standard, providing a structured framework for organizing relevant terms This model incorporates tools necessary for each stage, positioning ISO 9001:2008 as an international benchmark for quality management systems It serves as a comprehensive guide for process operations, particularly in demonstrating compliance with maintenance functions Ultimately, this results in a maintenance management model that synthesizes the best practices from the studied contributions while adhering to the principles of ISO 9001:2008.

This model begins and ends with the requirements and the satisfactions of the interested parties for proper maintenance management [15] Here, it takes the

‘‘interested parties’’ focus that is proposed by [13] The model is also designed to be effectively used in all levels of organization (reminding us of the proposals of

Effective business management operates on three levels of activity: senior management oversees strategic planning, while middle management focuses on support processes and maintenance control This structure generates essential data that drives continuous system improvement and facilitates ongoing replanning.

Likewise, the way in which this model is structured makes possible the existence of a link between function of maintenance and the rest of the organizational functions.

4.4 Maintenance Management Models Comparative Analysis 61

Maintenance Management and ICTs

E-technology integrates ICTs and new technologies, relying on intranet, extranet, and Internet connectivity along with electronic devices such as sensors and PDAs This integration enhances the ability to utilize diverse data sources, process large volumes of information, and conduct advanced analyses to support decision-making and collaborative activities The infrastructure of e-technology comprises essential resources, including applications, services, and devices, enabling remote operations through Mobile Collaborative Technologies (MCTs) These technologies facilitate optimal data integration and adaptability to various operational environments while ensuring real-time monitoring and diagnostics of equipment conditions The infrastructure is designed to maintain service quality, focusing on scalability and availability to provide timely responses for both companies and clients, measured through Key Performance Indicators.

Key Performance Indicators (KPIs) are essential for assessing global process performance and comparing it to expected outcomes Recent advancements in mobile collaborative technologies (MCT) have the potential to transform industrial asset management significantly By integrating wireless sensors, networks, and mobile devices, MCT effectively addresses the information access challenges faced by many organizations Notable features of MCT include enhanced connectivity, real-time data access, and improved collaboration among teams.

The influence of all these capabilities is even more important when the tasks are characterized by the immediacy and the high mobility of the involved staff [21].

The rapid convergence of technologies is leading to a greater sharing of key features among various mobile devices, including PDAs, tablets, smartphones, and ultra-portable laptops (UPL) This advancement in mobile technology significantly impacts our lives by breaking down space-time barriers and enabling the creation of intelligent user interfaces that provide contextually relevant information for different operations Numerous innovative products are now part of the e-technologies family, showcasing the evolution of mobile devices.

New intelligent MEMS sensors, including autonomous microsensors and memory cells, along with wireless sensors and sensor networks, play a crucial role in electronic technologies These sensors enable real-time monitoring of the operational conditions of devices, making them essential for effective process management.

RFID labeling is essential for identifying both the operator and components of a unit through geolocation This technology enables the storage of data regarding the performance and functioning of devices, facilitating the tracking of actions and operations performed, such as maintenance activities.

• Global positional system (GPS), in addition to the labels RFID, it is used for the calculation of location of an operator or the necessary tools.

Wireless technologies offer significant cost savings and unparalleled flexibility compared to traditional cable systems Key wireless technologies include standards like IEEE 802.11, ZigBee (802.15.4), and Bluetooth (802.15.1).

Bluetooth; wireless local area network, such as WiFi, WiMax, GSM-UMTS (of long distance).

Innovative communication systems, such as virtual reality, enhance interactions between individuals and devices or among people themselves These systems enable the direct reception of information in various formats, including text, static images, or animated visuals, facilitating a more engaging and immersive experience.

• Tools for the intelligent diagnosis and prognosis provide support to the decision- making process.

PDA, smartphones, graphic tablets, and laptops equipped with WiFi, Bluetooth, and RFID readers, along with Windows Mobile, enhance the efficiency of operators by enabling a wide range of functions that facilitate task execution with minimal time requirements.

Integration and interoperability standards among ICT components are essential for effective electronic technologies Key frameworks include MIMOSA (Machinery Information Management Open Systems Alliance), IEC 62264, and the OPC Foundation, which promote open connectivity and seamless communication between systems These standards ensure that various technologies can work together efficiently, enhancing overall operational performance.

Web services utilize a set of technical norms and standards, primarily based on Internet-based technologies, to facilitate data exchange between applications in diverse environments Key technologies driving this functionality include Simple Object Access Protocol (SOAP) for message exchange and Web Service Description Language (WSDL) for service description By leveraging these standards, web services enable efficient control, diagnosis, prognosis, and planning across heterogeneous systems.

Web-CMMS, also known as e-CMMS, is an advanced computerized maintenance management system designed to oversee and optimize preventive maintenance activities within a company This innovative system includes features such as application service provider (ASP) capabilities, enabling seamless integration with mobile technologies for efficient data retrieval and transmission.

The integration of various technologies into a unified infrastructure has led to the emergence of terms prefixed with "e-", such as e-maintenance for maintenance management and e-warranty for warranty management This shift not only redefines these processes but also establishes an e-platform that supports both maintenance and warranty management.

The increasing demand for information and advancements in Information and Communication Technology (ICT) are transforming business processes across various sectors The integration of ICT is driving significant changes in management practices, including areas such as e-business, e-operation, e-manufacturing, e-production, and e-maintenance.

E-maintenance is a modern maintenance management concept that utilizes the Internet to control and manage assets effectively It encompasses various strategies, including real-time data management from equipment through digital technologies, and incorporates techniques such as Condition-Based Maintenance (CBM), proactive, and predictive maintenance This interdisciplinary approach focuses on supervision, diagnosis, prognosis, and control, aiming to minimize on-site inspections and eliminate unnecessary maintenance activities.

E-maintenance enhances traditional maintenance practices by integrating web services and collaborative principles, facilitating the exchange of knowledge and intelligence among various units and departments This approach fosters improved decision-making throughout the asset life cycle by replacing conventional hierarchical structures with intelligent systems By leveraging electronic technology, e-maintenance provides real-time communication and information exchange, enabling optimized maintenance prioritization through a predefined alarm system that monitors equipment conditions Additionally, the costs based on criticality (CBC) framework incorporates equipment health, maintenance costs, production loss costs, and risk factors, leading to significant improvements in maintenance efficiency.

The Warranty Management Process

Management is defined as the process of leading and directing an organization, encompassing activities that establish targets, strategies, and responsibilities This involves implementing planning, control, supervision, and economic considerations In the context of warranty management, it refers to the structured actions and stages necessary to effectively oversee a warranty program This management approach is particularly relevant for a newly launched product, integrating both production and post-production activities.

Strategic management encompasses various focuses, as detailed in Refs [24, 25] From a strategic perspective, warranty program management initiates with a strategy that integrates technical and commercial planning right from the outset of the product development process, as illustrated in Fig 4.3.

In many cases, the steps in the warranty management process occur simultaneously, with after-sales support often provided while the production line is still active This allows valuable insights from after-sales service to inform production and enhance product design and development To effectively characterize these processes, a proposal for a reference framework is presented, utilizing various representation tools.

Our reference framework is defined by specific boundary conditions, illustrated in Fig 4.4 This black box representation (level 0) will undergo detailed analysis (level 1 and level 2) using standard integrated definition methods (IDEF) These methods are user-friendly and facilitate the clear representation of each component within our framework, including inputs, outputs, resource utilization, and signal controls, all of which have been simply implemented in this document.

The management of a warranty program plays a crucial role in influencing the product life cycle, and it is guided by various international standards that aim to streamline business activities through a series of interconnected processes.

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d defined in such standards and quality management systems usually fulfills the following features [32]:

• Factual approach to decision-making.

Particularly, the EN-ISO 9000 [33] defines a quality management system, which is designed to attend the needs of all interested parties: customers, suppliers, employees, and owners.

Implementing a process-based quality management system tailored to warranty management can enhance performance, as illustrated in Fig 4.5 This improvement strategy aligns with the principles of the Deming cycle, facilitating continuous enhancement in quality management practices.

Front-End Design & Development LAUNCH

Fig 4.3 Life cycle from a warranty perspective (adapted from [24])

Resources: ằ Internal / External ằ Technical / Human

Fig 4.4 Representation of boundary conditions of the framework (Level 0)

The Plan-Do-Check-Act (PDCA) cycle emphasizes the importance of warranty data in its process This data is primarily gathered from customer claims during warranty services, supplemented by additional relevant information.

Future research should focus on data requirements and their impact on analysis and consequences The flexibility of standards allows for adjustments in the warranty management process, making it applicable to any organization, regardless of size or type This article justifies the selection of four key steps in the warranty management process—effectiveness, efficiency, assessment, and improvement—on which our proposed framework will be built.

The effectiveness of a warranty program is crucial for enhancing customer satisfaction and reducing associated costs This involves defining clear objectives, priorities, and strategies, as well as identifying key performance indicators Early intervention in addressing identified weaknesses is essential to meet customer needs effectively The success of the after-sales department hinges on the quality of service from the customer's perspective, ultimately leading to lower warranty costs and improved customer satisfaction In essence, warranty effectiveness is determined by how well the company’s assets meet user needs, ensuring that product service is readily available when required Thus, the focus remains on the accuracy of the warranty process and its ability to deliver the desired outcomes.

Information flow Value-adding activities

Fig 4.5 Approximation of a warranty management process, according to ISO

The efficiency of a warranty program is crucial for minimizing waste, expenses, and unnecessary efforts while providing optimal service at the same cost This efficiency can be measured by comparing the planned resources for warranty tasks with the actual resources used By focusing on this efficiency, companies can achieve significant improvements in reliability and effectively define warranty plan activities within the after-sales department.

The third managerial block focuses on assessing the warranty program, which requires suitable measurements defined during the program's strategy phase These measurements should facilitate the comparison of reliability data and incorporate life cycle cost assessments Warranty program assessments should be conducted after warranty assistance or through regular product performance reviews Companies must establish a standardized, repeatable method for data collection, analysis, and interpretation, drawing on corporate or industry factors The findings should be utilized to support and justify program enhancements.

The fourth step focuses on enhancing the warranty program through established management performance indicators Given the extensive data generated from previous steps, a computerized information system is essential for managing warranty data and analyzing results effectively This includes the implementation of e-warranty, which leverages information technology to integrate diverse data sources, enabling the processing of larger data volumes and facilitating advanced decision-making E-warranty enhances after-sales service by improving data storage and analysis related to customer claims, thereby fostering continuous improvement in the warranty program.

The outlined process, divided into four steps, provides a straightforward representation of various data exchange connections, which can be beneficial for companies in effectively organizing warranty programs and managing field-related information.

Chapter 5 will provide an in-depth analysis of each phase, offering a comprehensive representation of all stages within the proposed framework The practical application of this framework will be explored in subsequent chapters, emphasizing the crucial role of the client in the warranty management process Given the complexity of the structure, it is logical to conclude that the final contextual element for applying this framework will be industrial customized products characterized by high levels of technology and sophistication, such as aircraft, defense systems, naval machinery, agricultural equipment, and construction machinery.

Commun icated complain ts Efficiency

Level 1 Ident if ication o f failur e root c a use spec ial ly in crit ical eq ui pm ent

In c ide nc es ri sks

Busi ness req u ir em ent s and r e st ri c tio ns

Re q u e s ted warr an ty serv ic es KPI T arg ets Action Plans Im p rov em en t pro p o s a l Re s o u rces assign me n t De tail ed warranty assistan ce program

S tan dard s and meth o d s T e c hnic a l and h u man re sources availab le Inc ide nc es cos ts

Inc ide nc es ri sks Critic ality matrix Warr an ty program cost eval uatio n

T e c hno lo gy wat c h S tan d a rd s and meth o d s

Busi n ess r e q u ire me nts and restr ictions Re p a ir qu al it y

S u gg e s ted freq ue ncy o f tasks Recommen d e d spares

Items h istorical re liab ility De pe n d abi lity & L C C outp ut d ata

New e-tech strategy sug g est io n Market in g data / Custo m er satisfac tio n Items h istori c al failur e data F ail ure info rmatio n

Improve m e n ts proposals Technical u p date Us age patte rn s Cost and ris k re d u ction

Cost and ris k re d u ction Claims fo re cast Improve m e n t pro p o s al

Effectiveness Assessment Improvement Fig 4.6 Relationship and exchange of information between steps ( Level 1 )

1 AENOR 2010 Norma UNE-EN 13306 Terminología De Mantenimiento.

2 AENOR 2008 Norma ISO 9001 Sistemas De Gestión De La Calidad.

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13 Sửderholm P, Holmgren M, Klefsjử B 2007 A Process View of Maintenance and its Stakeholders Journal of Quality in Maintenance Engineering 13(1):19–32.

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Effective management processes can be divided into two key components: strategic planning and execution In the context of managing a warranty program, the strategic phase involves setting warranty targets aligned with the business plan These objectives focus on reducing costs while ensuring the procurement of reliable products and providing excellent after-sales service to customers.

Management Framework of a Warranty

This section introduces various blocks and methods to enhance decision-making in after-sales service, focusing on a reference framework for warranty management that supports engineering and manufacturing phases While the document highlights specific tools and techniques, it emphasizes that many other relevant methods exist In addition to product reliability, considerations must also include overall operations like production and services The development of joint strategies for improving warranties on existing products and for new products is essential Given the complexity of this field, the document aims to succinctly present key information, with references to additional sources for further exploration.

5.1.1 First Step: Warranty Program Effectiveness

To prevent contradictions in the warranty strategy program and align it with the company’s overall management, the study recommends implementing a balanced scorecard (BSC) This methodology focuses on setting goals and targets from four distinct perspectives, as illustrated in Fig 5.2.

Fig 5.1 ‘‘Doing’’ and ‘‘thinking’’ in warranty management (adapted from [2])

BSC applied to the management of a warranty program can involve the following steps:

(a) Strategical formulation for the warranty program (such as the outsourcing [7] of warranty assistance or the development of warranty teams with multiskilled technicians).

(b) Translation of warranty strategic into middle-term reachable objectives (such as the identification of measures designed to pull people toward an overall vision).

(c) Development of action plans (in order to reach the targets identified in step b, and taking into account any necessary changes in the organization’s support infrastructure).

(d) Periodical review of performance and strategy (just to quantify the progress in order to formulate new strategic objectives, action plans, or the revision of the whole scoreboard).

After defining the objectives and strategies of the warranty program, it is essential to assess product criticality, which refers to the significance of customer complaints and their potential impact on the business This criticality analysis informs decisions within the warranty program, as it may lead to deviations from business goals, including profit losses, resource reallocation, and delays To effectively prioritize assets in warranty management, a systematic approach is necessary, aligned with the program's strategy One effective technique for this prioritization is risk-cost assessment, which evaluates the likelihood of issues alongside their associated costs.

Ability to improve and create

Achievement of financial and customers objectives

Performance attributes valued by customers

Objectives Measurements Targets Initiatives Investor s point of view

Fig 5.2 Perspectives to reach goals by a balanced scoreboard5.1 Management Framework of a Warranty Assistance Program 75

We developed a criticality matrix to prioritize probable warranty-related events, enabling us to align after-sales actions with business objectives and effectively assess the impact of these occurrences.

By strategically allocating resources to mitigate risks, businesses can reduce warranty costs and enhance customer satisfaction Once a clear strategy is established and potential events prioritized, it becomes crucial to address customer complaints regarding recurring or chronic failures, which are high-priority issues Timely identification and elimination of the root causes of these failures can offer significant initial benefits to the warranty program strategy.

Various methods have been developed to analyze weak points, such as failure root cause analysis, which identifies the reasons behind specific failures and how to address their causes A primary classification of these causes can determine whether the failure requires warranty attention This analysis aids in adjusting the initial considerations of the balanced scorecard, thereby enhancing the effectiveness of the warranty program A comprehensive root cause failure analysis typically includes several key steps.

• Determining a root cause of failure;

• Proposing, testing, and validating hypotheses;

• Analyzing the results and determining failure causes.

Causes still unknown ằ This area reduces itself by the experience ằ Related costs are in principle unexpected

Causes already known ằ First approach based on maintenance data ằ Related costs are under control ằ ằ ằ First approach based on ằ

Fig 5.3 First classification of causes

After all that has been stated here, the effectiveness of a warranty program could require specific information (inputs) and also provide determined results (outputs) that can be summarized in Table 5.1.

This sample data demonstrates how the proposed methodologies can be effectively applied in a typical company that sells industrial products The specific inputs and outputs will vary based on the unique characteristics of the organization and the specific conditions under which it operates its commercial and industrial activities.

5.1.2 Second Step: The Efficiency of the Program

To optimize warranty management while minimizing waste and costs, it is essential to develop a comprehensive warranty program plan This plan should identify the product's functions, potential failure modes, and establish effective tasks that prioritize safety and service efficiency Implementing management techniques from the maintenance sector, such as an adapted Failure Mode, Effects, and Criticality Analysis (FMECA) or Reliability-Centered Maintenance (RCM), can significantly enhance the initial stages of the warranty program.

Table 5.1 Inputs/outputs in the effectiveness of a warranty program

Balance scorecard • Incidence risks • Selection of KPI

• Required warranty services Criticality analysis • Selection of KPI • Matrix of criticality

• Failure information Failure root cause analysis

• Matrix of criticality • Identification of the failure root in critical equipment

• Standards and methods5.1 Management Framework of a Warranty Assistance Program 77

FMECA plays a crucial role in designing a generic maintenance plan, particularly during the warranty period An initial maintenance strategy can effectively support warranty capacity planning, spare parts provisioning, task scheduling, and technician skill level requirements Enhancing planning and scheduling within a warranty program can significantly improve its effectiveness and efficiency, with the extent of improvement influenced by the analysis time horizon Additionally, various analytical and empirical approaches exist for cost and failure modeling, drawing from diverse fields.

In order to carry out a Warranty Policy Risk-Cost-Benefit Analysis, such activity will depend of course on the objective that the own model builder keeps in mind.

Previously in Chap 3, in Fig 3.9, an integrated model for total warranty costs is presented.

The management of a warranty program is significantly impacted by the available information, which often adds complexity to the issue To effectively analyze the situation, certain assumptions may need to be made to simplify the resolution or minimize computational demands Similarly, just as in an effectiveness program, achieving efficiency requires specific information to yield clear results, which can be exemplified for a typical company as illustrated in Table 5.2.

Inputs and outputs will also depend on the particular organization as well as on the boundary conditions where the company develops its commercial and industrial activity.

5.1.3 Third Step: The Evaluation of the Program

After designing, planning, and scheduling the warranty program activities, it is essential to execute these tasks and evaluate their performance Additionally, conducting a reliability, availability, maintainability, and safety (RAMS) analysis is crucial, given the numerous restrictions and conditions that must be considered.

3 What does the failure cause?

4 What happens when it fails?

6 What can we do to prevent the failure?

7 What can we do if it is not possible to prevent the failure?

Failure knowledge comes from a costumer complaint

Mainten anc e Design Tools for Warranty

Fig 5.4 Application of maintenance techniques to warranty casuistry

The complex product currently available on the market encompasses various components and subsystems, each presenting potential failure modes that must be addressed during the design phase, as outlined in standards like ISO 14224/2000 Conducting a RAMS analysis provides insights into the product's performance capabilities under specific conditions and over a designated timeframe, allowing for the assessment of how long a system or component can function before requiring maintenance or replacement This analysis also evaluates the product's resilience against failures and other undesirable incidents, often quantified in terms of probability by examining the cause-and-effect relationships of failures Additionally, leveraging warranty program data during the ongoing production phase can enhance product engineering and manufacturing Reliability assessments can significantly inform design modifications, highlighting potential incompatibilities with initial technical specifications early in the product development process For already launched products, such analysis aids in implementing timely improvements and addressing user claims related to reliability discrepancies compared to earlier models.

Table 5.2 Inputs/outputs in the efficiency of a warranty program

RCM adapted to warranty • Failure root identification in critical equipment

Warranty policy of cost risk benefit analysis

• Availability of technical and human resources

5.1 Management Framework of a Warranty Assistance Program 79

In the third step of warranty program assessment, conducting a life cycle cost analysis is crucial, as it evaluates the total cost of a product throughout its lifespan This analysis encompasses various expenses, including planning, research and development, production, operation, warranty, and disposal costs For consumers, life cycle costs reflect acquisition expenses, purchase price, and ongoing maintenance, representing the overall ownership cost Warranty-related life cycle costs are significantly affected by factors such as reliability, failure rates, spare part costs, repair times, and component expenses Typically, insufficient product engineering budgets result in elevated warranty costs later on Promptly addressing customer complaints regarding significant failures is essential, as it allows for thorough analysis and identification of not only necessary repair actions but also preventive measures to reduce future claims.

Conducting a root cause failure analysis, as outlined in step 1, is essential for addressing warranty complaints By thoroughly reviewing these complaints, one can identify recurring failures and trends associated with vendor and buyer issues, quality concerns, manufacturing conditions, and product design flaws.

Table 5.3 provides a sample of the information that can be required or obtained in the assessment and control step of a warranty program for a generic company.

Data ằ Vendor data ằ Test data

Prototype ằ Reliability development ằ Product implications ằ Testing model ằ

Reliability models ằ Testing model ằ Assessment model ằ Vendor data ằ Test data

Prototype ằ Reliability development ằ Product implications

Component reliability Reliability development Constraints

Prototype ằ Reliability development ằ Product implications

Fig 5.5 Reliability assessment and the product development (adapted from [10])

The continuous improvement of warranty program management is enhanced by the integration of emerging technologies, leading to the concept of "e-warranty." This innovative approach, part of e-manufacturing, leverages advanced information and communication technologies to create a collaborative multi-user environment E-warranty encompasses the necessary resources, services, and management for proactive decision-making, incorporating activities like e-monitoring, e-diagnosis, and e-prognosis Additionally, the active participation of after-sales technicians is crucial in refining the warranty process, ensuring high product quality and efficient technical assistance services.

Consequently, higher levels of knowledge experience and training will be required.

Integral Representation of the Warranty

The proposed warranty management framework reaches optimal maturity through a cyclical process that aligns decisions with the overarching business goals By utilizing both quantitative and qualitative feedback, it enhances the production system while incorporating established technologies from other sectors.

In this section, we will characterize the warranty management process using integrated definition (IDEF) methods, as illustrated in Figs 4.4 and 4.6 from the previous chapter These user-friendly representation tools will allow us to depict each stage of the warranty management framework through charts that clearly outline the inputs, outputs, and processes involved.

Table 5.4 Inputs/outputs in the enhancement of a warranty program

• Assessment of warranty management program

• Data of ‘‘dependability’’ and CCV

• Patterns of actions and claims

Six Sigma • Assessment of warranty program costs

The after-sales department must operate within a business plan and align with company objectives Once the strategy is defined, it is crucial to implement it while considering organizational constraints This involves identifying necessary functions to execute the strategies and categorizing them into processes and activities The overall warranty management process can be structured into distinct blocks, similar to those suggested for maintenance.

The goal is to create a process diagram that clearly outlines the various stages of the proposed framework The key processes and activities will mirror those found in maintenance Table 5.5 presents the essential and shared activities related to warranty within the proposed framework, illustrating their connection to each phase of the reference model.

Technical performance varies between companies for each activity These blocks illustrate distinct processes tailored to specific warranty management scenarios, each requiring unique resources and influencing service quality differently Their effectiveness depends on the underlying knowledge and the level of control available.

The coordination of interactions among warranty functions is essential to the strategy organization, facilitating effective warranty management This process improves collaboration with other organizational functions, thereby enhancing knowledge management within the company.

Maintenance Design Tools adapted to Warranty

Warranty Policy Risk-Cost- Benefit Analysis

Reliability, Availability, Maintenability and Safety

Customer Relationship Management E-Technologies (ICT’s)

Fig 5.9 Framework proposal for a warranty management program5.2 Integral Representation of the Warranty Management Framework 85

From an operating point of view and according to the responsibilities involved, three possible interactions are here presented among the warranty processes:

1 A first possible interaction is when a complaint is communicated by a customer which must be answered by warranty assistance.

2 A second possible interaction in case of an incident not detected because a complaint from a customer, but through (for instance) a proactive (e-warranty) or a detection during another intervention.

3 Finally, activities from the after-sales department are also requested when there is any modification in parts of the product already in the market When it happens, this is usually due to mistakes in product design or failures in a product batch Many of these types of activities are sometimes approved to be accomplished during preventive maintenance actions.

Table 5.5 Inputs/outputs between stages of the proposed framework

Warranty Policy Risk-Cost-Benefit Analysis

Reliability, Availability, Maintenability and Safety

Life Cycle Cost Analysis E-Warranty

Effective Customer Relationship Management (CRM) involves strategic KPI selection to assess warranty program costs Utilizing a criticality matrix aids in identifying the root causes of failures, particularly in essential equipment Accurate estimation of resources and repair quality is crucial to minimize incidence risks and associated costs Recommended spares and suggested task frequencies enhance dependability, ensuring optimal equipment performance and longevity.

The analysis of LCC output data reveals critical insights into historical failure data and usage patterns, which inform claims forecasts and enhance the new e-tech strategy By examining failure information and implementing technical updates alongside 6S improvement proposals, organizations can achieve significant cost and risk reduction Adhering to established standards and methods, while leveraging available technical and human resources, ensures effective technology monitoring and aligns with business requirements, ultimately addressing communicated complaints efficiently.

Table 5.5 encapsulates all inputs and outputs discussed in this chapter, highlighting the interactions between various methodologies and proposals The performance of organizations differs based on specific scenarios, emphasizing the need for tailored approaches To further illustrate these interactions, the next level (level 2) processes are depicted in Figs 5.10, 5.11, 5.12, and 5.13.

The representations in Figs 5.10 to 5.13 provide a simplified illustration of the interactions among the proposed stages, highlighting how each stage operates within its boundary conditions and the information flows it engages in, either as a receptor or generator This visual framework is based on standard IDEF methods, which are user-friendly and facilitate the representation of each stage in boxes that display various inputs and outputs.

23], applying here in a particular manner to serve our purposes of study.

The goal is not to rigidly adhere to the IDEF standard but to utilize its illustrative capabilities to present the information from Table 5.5 in a unique manner The numbering in circles within these four figures corresponds to the phases of the proposed framework, indicating the origin of the information or data.

Identification of failure root cause specially in critical equipment

KPI Targets Action Plans Improvement proposal

Fig 5.10 Integrated representation of level 2A: effectiveness5.2 Integral Representation of the Warranty Management Framework 87

Maintenan design tools adapted to Warranty

Warranty Policy Risk- Cost-Benefit Analysis

Technical and human resources available

Maintenan design tools adapted to Warranty

Warranty Policy Risk- Cost-Benefit Analysis

Technical and human resources available

Fig 5.11 Intergrated representation of level 2B: efficiency

8 ằ Recommended spares ằ Suggested frequency of tasks

Reliability, Availability, Maintenab and Safety

8 ằ Recommended spares ằ Suggested frequency of tasks

Fig 5.12 Integrated representation of level 2C: assessment and control

This study initially aimed to apply civil industry tools to the defense sector, highlighting the importance of software packages that organize extensive interactions and information These tools are particularly beneficial for managing complex military assets, including combat vehicles, armored boats, and military transport airplanes.

Framework Implementation

The implementation of the proposed warranty management framework necessitates specific conditions and characteristics to ensure its successful application in real-world scenarios.

1 General support of the organization: The implementation of this framework requires the agreement, support, and comprehension of the whole company.

2 Complex industrial assets: This framework will be useful when the product is highly complex and technologically sophisticated.

Communicated complaints Business requirements and restrictions

Fig 5.13 Integrated representation of level 2D: continual improvement5.2 Integral Representation of the Warranty Management Framework 89

3 Supporting information systems: It is mandatory that all the applied information systems should be appropriate to coordinate and organize large amounts of data as well as different involved areas Specifically, the application of information systems can be organized into three main modules: logistical support analysis (LSA), provisioning, maintenance and supporting services management, as well as two additional modules: technical documentation and e-learning (Table 5.6).

4 Training staff and managers: The people in charge of making decisions in the field of application of this reference framework have to be trained in all supporting techniques and methodologies, also to be needed to be provided with a proper vision of the warranty management framework.

5 Training of technical staff: Complementing the last paragraph, personnel performing warranty interventions have to assure an accurate data collection (symptoms, ways of failure, causes, etc.).

6 Assurance and commitment in the control: It is important to guide and properly manage the warranty program at a tactical, operative, and strategic level within the applied and proposed reference framework.

The "Eagle Tool Kit," developed by [24], exemplifies a successful application of the warranty management framework This efficient information system aids businesses in creating, managing, and delivering essential support services.

Table 5.6 Modules of supporting information systems Logistic support analysis

Management of logistic support analysis (LSA)

Integration of data from LSAR

Creation of the illustrated catalog of replacements

Operational use of failure follow-up

Knowledge database of SGML/XML

Reuse of content in technical publications Maintenance task analysis

Interaction with the supply chain

Model of content in XML Generation of task modules

Exchange capabilities and management of parts

Support to pedagogical structured objects

Standards for logistic data of products

Logistical data is essential for government agencies, contractors, service suppliers, and companies globally, facilitating the management of integrated logistical support (ILS) for operational equipment and assets in accordance with military standards This framework primarily addresses warranty management for complex industrial assets during their operational phase However, it is also applicable in the preoperative phase, allowing for the prediction of industrial asset behavior during design and development before market launch.

1 Crespo Márquez A, Moreu P, Gómez J, Parra C, González-Prida V 2009 The maintenance management framework: A practical view to maintenance management Taylor & Francis Group, London, ISBN 978-0-415-48513-5 Pp 669-674.

2 Crespo Márquez A 2007 The maintenance management framework: models and methods for complex systems maintenance Springer-Verlag London Limited ISBN-13:

3 Murthy DNP, Rausand M, Osteras T 2008 Product Reliability - Performance and Specifications Springer Verlag, London Pp 284+xvii.

4 Murthy DNP, Rausand M, Virtanen S 2009 Investment in new product reliability, Reliability Engineering & System Safety 94:1593-1600.

5 Murthy DNP, Hagmark PE, Virtanen S 2009 Product variety and reliability Reliability Engineering & System Safety 94:1601-1608.

6 Murthy DNP, Osteras T, Rausand M 2009 Component reliability specification Reliability Engineering & System Safety 94:1608-1617

7 Gómez J, Crespo Márquez A, Moreu P, Parra C, González-Prida V 2009 Outsourcing maintenance in services providers Taylor & Francis Group, London, ISBN 978-0-415- 48513-5 Pp 829-837.

8 International Std 2004 ISO/DIS 14224, ISO TC 67/SC /WG 4 Petroleum, petrochemical and natural gas industries - Collection and exchange of reliability and maintenance data for equipment Standards Norway.

9 González-Prida V, Crespo Márquez A, Moreu P, Gómez J, Parra C 2009 Availability and reliability assessment of industrial complex systems: A practical view applied on a bioethanol plant simulation Taylor & Francis Group, London, ISBN 978-0-415-48513-5 Pp 687-695.

10 Murthy DNP, Blischke WR 2005 Warranty management and product manufacturing.

Springer-Verlag London Limited Pp 302+ xviii ISBN 1852339330.

11 Parra C, Crespo Márquez A, Moreu P, Gómez J, González-Prida V 2009 Non-homogeneous Poisson Process (NHPP), stochastic model applied to evaluate the economic impact of the failure in the Life Cycle Cost Analysis (LCCA) Taylor & Francis Group London ISBN 978- 0-415-48513-5 Pp 929-939.

12 European Std 2008 EN-ISO 9000 standards Quality Management System European Committee for Standardization, Brussels.

13 González-Prida V, Parra C, Gómez JF, Crespo Márquez A 2010 Reference framework proposal for the management of a warranty program Euromaintenance 2010 20th International Industrial Maintenance Congress in the Verona Conference Centre, Italy.

15 Giaglis GM 2001 A Taxonomy of Business Process Modelling and Information Systems Modelling Techniques The International Journal of Flexible Manufacturing Systems.

16 IEEE Std 1998 IEEE Standard for Functional Modelling Language -Syntax and Semantics for IDEF0 1320.1 New York: IEEE.

17 Kim SH, Jang KJ 2002 Designing performance analysis and IDEF0 for enterprise modelling in BPR Int J Production Economics 76:121-133.

18 González-Prida V, Barberá L, Gómez JF, Crespo Márquez A 2011 Contractual and quality aspects on warranty: best practices for the warranty management and its maturity assessment.

International Journal of Quality and Reliability Management, IJQRM.

19 Duffua SO, Raouf A, Campbell JD 2000 Planning and control of maintenance systems.

Indianapolis: John Wiley and Sons.

20 López M, Crespo Márquez A 2010 Modelling a Maintenance Management Framework Based on PAS 55 Standard Quality and Reliability Engineering International John Wiley &

22 Giaglis GM 2001 A Taxonomy of Business Process Modelling and Information Systems Modelling Techniques The International Journal of Flexible Manufacturing Systems.

23 Shoung-Hie Kim, Ki-Jin Jang 2002 ‘‘Designing performance analysis and IDEF0 for enterprise modelling in BPR’’ Int J Production Economics 76 121-133.

25 Department of Defense, USA, ‘‘Requirements for a Logistics Support Analysis Record’’

Auditing the Initial Case Study

In this chapter, we will analyze the case study from Chapter 3 as an audit, proposing improvement actions aligned with the reference framework outlined in Chapter 5 Our goal is to evaluate the support offered by various methodologies and tools suggested in the framework Additionally, this analysis aims to provide a comprehensive development of the framework, enabling future research to identify best and worst practices adopted by companies across different sectors.

Considerations to the Current Situation

This exercise assesses whether our organization is utilizing current techniques to effectively address existing issues or if there are areas within the decision-making process that require enhancement Tables 6.1, 6.2, 6.3, and 6.4 outline key weaknesses identified in the case study along with corresponding suggestions based on the proposed framework.

Improvement Actions

After pinpointing the areas for improvement, we can suggest actionable strategies to enhance warranty program management and optimize decision-making within our specified study context.

In the effectiveness stage checking phase, decisions are often reactive, responding to immediate issues rather than proactively preventing them Initially, the focus is on short-term objectives tied to an after-sales strategy, but there is a need for a strategic formulation of warranty programs that aligns with medium-term goals and includes actionable plans Regular performance reviews are essential to measure progress and adapt the organization's support infrastructure as needed Additionally, customer complaints are typically addressed using a FIFO method, highlighting a lack of clarity between clients and manufacturers regarding inoperability Managers in this area often struggle to balance these complaints with broader business objectives.

A systematic approach to prioritizing assets in warranty management can prevent inconsistencies with the current program strategy By evaluating the likelihood of events and their potential impacts, businesses can align after-sales actions with their objectives, enhancing overall effectiveness.

Repetitive and systematic failures require targeted interventions, yet the definition of systematic failure often lacks clarity, leading to delays in addressing these issues To expedite intervention, a structured root cause analysis protocol should be implemented, enabling timely responses and adjustments based on the initial assessments outlined in the balanced scorecard.

94 6 Auditing the Initial Case Study

To enhance warranty management across departments, a balanced scorecard model is recommended to align local objectives with overarching business goals This model should encompass the after-sales, logistics, manufacturing, quality, purchasing, and engineering departments, with objectives, measures, targets, and initiatives developed under management oversight and regularly reviewed to track progress and refine strategies Clear definitions of concepts between clients and manufacturers are essential to identify system failures and facilitate timely interventions Additionally, a Criticality and Failure Root Cause Analysis must be conducted using data on incidents, damaged materials, and repairs collected by the after-sales, quality, and engineering teams, all while adhering to the initial balanced scorecard considerations The quality department should oversee the ongoing review and compilation of these analyses and database records.

The implementation of warranty assistance has clarified the current warranty needs associated with the organization's support infrastructure This newfound clarity enables the performance of reliability analysis and a tailored risk-cost-benefit analysis related to warranties, facilitating more informed decision-making.

Phase Initial scenario Proposed framework

4 Maintenance techniques adapted to warranty

The maintenance criteria about capacity planning, the spare parts provisioning, the warranty task schedule, skill level of the technicians, etc., is applied during the whole warranty program

An initial maintenance plan, applied to the warranty time horizon, can suppose a good first approach.

Nevertheless, it is crucial for its adaptation to the warranty necessities

5 Warranty policy risk-cost- benefit

While a formal risk-cost-benefit analysis is absent, a cost provision is established at the project's outset Throughout the development of the warranty program, there is ongoing monitoring and adjustments to the initial budget allocated for warranty assistance.

An integrated model for total warranty costs relies on the available information, highlighting the complexity of the issue To effectively address this complexity, specific assumptions must be made, which can either simplify the analytical process or reduce computational requirements.

In the assessment stage, the proposed framework emphasizes the importance of RAMS analysis, which involves evaluating after-sales support while the production line remains active This analysis utilizes warranty program data to enhance product engineering and manufacturing, assuming uniform reliability across all vehicles Conducting this analysis early in a product's life is crucial, but it can also provide insights for improvements post-launch, addressing potential user claims related to initial reliability issues Consequently, this proactive approach boosts reliability and enhances customer satisfaction Additionally, life cycle cost analysis is initiated at the project's outset, integrating warranty costs as a percentage of the overall budget, ensuring a comprehensive understanding of the product's financial implications throughout its life cycle.

The life cycle cost associated with warranty issues is significantly affected by factors such as reliability, failure rates, spare parts costs, repair times, and component expenses As discussed in the article, insufficient funding for product engineering can result in increased warranty costs down the line Consequently, conducting a comprehensive life cycle cost analysis is essential for establishing an adequate budget to address potential future warranty requirements.

In the continuous improvement stage of the warranty process, it is crucial for technicians to possess high levels of knowledge, experience, and training to effectively utilize specialized tools and test equipment for vehicle assessments However, the integration of advanced technologies such as e-monitoring, e-diagnosis, and e-prognosis, which are essential components of the "e-warranty" concept, is currently lacking in implementation.

Implementing new technologies in a warranty program is essential for providing effective support This involves utilizing resources, management strategies, and services that facilitate proactive decision-making, ultimately leading to improved product quality and enhanced program effectiveness.

The integration of new technologies into warranty programs is essential for enhancing support and achieving higher product quality and program effectiveness This involves utilizing resources, management, and services to facilitate proactive decision-making Key improvements include identifying products that require attention and establishing faster communication channels, as well as segmenting client groups to tailor warranty strategies and optimize response times A robust database plays a pivotal role by offering valuable quantitative and qualitative insights, including statistical analyses Additionally, a dedicated management team is crucial for ensuring effective communication with clients and coordination among departments, enabling efficient order distribution and decision-making.

The proposed methodology requires however a multidisciplinary full-dedicated team, together with improvement tools, mainly statistical, in order to engage the complex mechanisms inside a company

Effective warranty program management requires careful capacity planning, spare parts provisioning, and scheduling of warranty tasks, all while considering the skill levels of technicians It is essential for various departments to monitor data that impacts their responsibilities as events evolve and conditions change The management team, in collaboration with the after-sales department, should regularly update resource allocations to ensure that current warranty needs are adequately met.

The warranty database, maintained by the quality department and enriched with data from after-sales, engineering, and manufacturing, serves as a vital tool for conducting Reliability, Availability, Maintainability, and Safety (RAMS) analyses and life cycle cost studies The findings from these analyses, expressed in probabilistic terms, highlight the relationships between failure causes and effects, enabling the engineering and manufacturing teams to implement design and assembly improvements that enhance product reliability This information is crucial for the management team to allocate appropriate budgets for future warranty needs and for the after-sales department to promptly address significant claims related to costly failures Additionally, the after-sales team can leverage these insights to identify preventive measures, ultimately reducing future customer complaints stemming from similar issues.

Quality and Maturity Aspects in Warranty Management

6.3.1 Standards and Best Practices for the Quality of Warranty Management

Currently, companies are implementing best practices in warranty management that address both business processes and quality assurance Adopting industry standards can significantly enhance warranty management, providing a competitive edge Key standards that exemplify these best practices include those outlined in Table 6.6.

The Baldrige National Quality Program and its prestigious Award enhance organizational performance by promoting best practices across various US organizations This program serves as a valuable tool for managing performance, guiding strategic planning, and fostering opportunities for continuous learning and improvement.

Total Quality Management (TQM) is a comprehensive management philosophy aimed at enhancing all aspects of a company, including marketing, finance, design, engineering, production, and customer service, to align with the primary goal of fulfilling customer needs.

The European Foundation for Quality Management (EFQM) empowers organizations to enhance their management performance through continuous improvement in processes and quality By facilitating networking opportunities and mutual learning experiences, EFQM supports the adoption of best-in-class tools, driving organizations towards higher levels of excellence.

Table 6.5 illustrates the involvement of various departments—Logistics, Manufacturing, Administration, After Sales, Quality, Purchasing, and Engineering—across different phases of the framework The effectiveness of each department is assessed using the balanced scorecard, revealing varying levels of criticality and engagement Notably, Manufacturing and Quality departments show high involvement in criticality analysis and failure root cause analysis, while Purchasing and Engineering are significantly engaged in warranty policy and risk-cost-benefit analysis Efficiency is enhanced through maintenance design tools, with Administration and After Sales also playing important roles Reliability, availability, maintainability, and safety assessments indicate substantial participation from Manufacturing and Quality The life cycle cost analysis sees a moderate contribution from various departments, while improvement initiatives, particularly in e-technologies and customer relationship management, highlight a collaborative effort across the board, with Six Sigma practices being uniformly adopted.

ISO 9000 is a comprehensive set of standards focused on process management and quality assurance, established by the International Organization for Standardization It outlines essential procedures that encompass all critical business processes to ensure their effectiveness Additionally, it emphasizes the importance of regularly reviewing the quality management system to enhance its efficiency and support ongoing improvement.

The Committee of Sponsoring Organizations of the Treadway Commission (COSO) is a prominent private sector organization that offers essential guidance on various aspects of organizational governance, including business ethics, internal control, enterprise risk management, fraud prevention, and financial reporting.

• TL 9000 is a quality management practice created to focus on supply chain directives, mainly for the international telecommunications industry [13].

No single model is universally applicable in all situations; thus, standards and reference frameworks should enhance business processes and overall productivity The proposed framework must incorporate elements of these standards to better address specific challenges A process is defined as a series of logically related tasks aimed at achieving a particular business outcome Additionally, it involves the organized interaction of personnel, materials, energy, equipment, and procedures to achieve a defined final result.

Effective warranty management should be approached as a redesign utilizing an integrated methodology to enhance process performance in terms of cost, quality, service, and speed This involves a dual perspective on each process: a strategic view that emphasizes its contribution to the business and an operational view focused on execution The proposed warranty management framework addresses both perspectives by incorporating activities that ensure quality in warranty services, thereby streamlining decision-making and identifying areas for improvement Ultimately, the framework aims to be customer-centric, process-oriented, and service-focused Additionally, the Capability Maturity Model Integration (CMMI) serves as a valuable framework for further process enhancement.

Table 6.6 Standards and international practices (adapted from [14])

6.3 Quality and Maturity Aspects in Warranty Management 101

The article discusses the importance of warranty assistance in customer service and outlines essential management elements necessary for achieving a specified level of maturity It highlights the Capability Maturity Model Integration (CMMI) as a framework to assess areas related to warranty management, quantifying maturity across five progressive levels to enhance process efficiency.

It represents a process with unpredictable result The process is unstable and unorganized It is defined by who performs it without explicit procedures.

It represents a process characterized by repeatable performance The process is planned, implemented, monitored, and checked according to predefined objectives.

The process involves a structured implementation program within the company, grounded in clearly defined methodologies, techniques, and supporting technologies Established procedures are essential to effectively drive this process forward.

The process is meticulously managed using quantitative techniques and, when necessary, statistical analysis Business objectives are evaluated through a thorough understanding of the outcomes derived from this quantitative analysis.

To ensure continuous improvement in alignment with business objectives, a corporate policy is implemented to manage process quality through quantitative data and feedback This approach facilitates the testing of new methodologies, techniques, and technologies.

6.3.2 Best Practices Applied to the Warranty Management Framework

In order to support our framework on the selected international frameworks, we have selected mainly widely extended and general practices:

The EFQM model, established in 2006 by the European Foundation for Quality Management, serves as a key reference for organizations aiming to enhance their management practices It focuses on driving continuous improvement and achieving both internal and external efficiency by effectively coordinating company activities and resources.

• ISO 9001 (2008): The family of ISO 9000 is a list of procedures about ‘‘quality management’’ used to develop the proposed reference framework, as a guide for quality and processes orientation.

Total Productive Maintenance (TPM), developed by the Japanese Institute of Plant Maintenance (JIPM), focuses on enhancing machinery performance by minimizing quality failures, breakdowns, and accidents This maintenance program aims to boost productivity and employee motivation while maintaining high-quality standards.

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d maintenance, giving a special attention to the personnel knowledge which can be adapted for the warranty management.

Development of the Framework Stages

The Balanced Score Card in After-sales Management

The Balanced Scorecard (BSC) is a multidimensional methodological tool that integrates corporate strategies with operational activities to set organizational objectives and assess business performance through management indicators By facilitating the implementation of strategic directives from management, the BSC aligns departmental targets with overarching strategic goals while monitoring deviations It serves as a communication, information, and training system for company strategy, complementing traditional strategic planning processes This methodology translates vision and strategy into a set of objectives and performance indicators organized across four key perspectives essential for effective management and control.

1 Perspective of learning and growth The objective is to assure the capacity of adaptation and long-term renovation of the company (in response to the various changes in the field), as well as to keep knowledge of the areas considered as basic competencies.

2 Perspective of internal processes It considers quality, productivity, and costs of distinct objective processes developed by the company, among them, the processes of maintenance management and warranty reclamation management (number of defective units, productive life cycle, idle capacity of equipment, etc.

3 Perspective of customers It evaluates the way in which the company generates value for the customers It seeks to measure the impact and satisfaction that the company generates on its customers.

4 Financial perspective It measures survival, growth, and development of the company in financial and value generation terms.

The Balanced Scorecard (BSC) integrates technical and financial measurements with broader metrics that connect internal processes and employee performance to long-term success By complementing financial indicators, the BSC clarifies and transforms a company's vision and strategy, enabling the identification and planning of strategic initiatives Clearly defined indicators are essential for measuring associated objectives, allowing for effective strategic tracking and evaluation by designated personnel responsible for compliance Each initiative, indicator, and objective is assigned to an individual to ensure accountability and progress monitoring.

Strategic initiatives are established to achieve specific objectives and targets, taking into account the implementation efforts and the benefits derived from these actions.

To ensure the effective execution of strategic objectives, a periodic follow-up system should be established, enabling timely decision-making and adjustments to the defined strategy Key performance indicators (KPIs) in the Balanced Scorecard (BSC) methodology must be relevant, practical, measurable, and implementable, facilitating data-driven decision-making and strategic alignment.

The Balanced Scorecard (BSC) framework includes two types of indicators: lag measurements, which reflect past results and provide insights into previous decisions, and lead measurements, which assess current process performance and enable proactive adjustments for improvement It is crucial for the BSC to maintain a balance between these measurements, as lead indicators are more predictive and facilitate quicker responses To effectively implement these indicators, they must be integrated with existing company information systems, and the necessary data sources along with their appropriate frequency must be clearly identified.

INTERNAL PROCESSES Fig 7.1 BSC perspectives

7.1.2 BSC Principles in Global Warranty Management

The Balanced Scorecard (BSC) enhances dialogue and communication across all company areas, including after-sales service, fostering greater participation, alignment, and synergy By managing technical and financial indicators, companies can establish a unified language for after-sales services Key financial perspectives, customer insights, process improvements, and learning metrics enable the calculation of availability through average repair and failure times, thus optimizing the relationship between production, sales, costs, and availability A primary goal of the BSC in warranty services is to convert strategic sales objectives into actionable plans, guided by key performance indicators derived from the four perspectives of the methodology.

The process involves establishing measures, targets, and action plans to achieve company objectives, ensuring alignment in management strategies This alignment is facilitated by developing key performance indicators through functional measures that closely relate to the results obtained in various processes, making them easier to measure and control.

The Balanced Scorecard (BSC) facilitates the comprehensive implementation of maintenance strategies across all organizational levels, promoting the active involvement of all stakeholders in achieving strategic objectives This approach ensures strategic alignment throughout the organization by transforming specific action plans into effective strategies.

7.1.3 Application to Improve Effectiveness in Warranty Management

This methodology aligns the local objectives of a department or business unit with the overarching goals of the company, particularly in warranty management By utilizing the Balanced Scorecard (BSC) principles within a framework of continuous improvement, potential conflicts between warranty programs and the company's global strategy can be mitigated The BSC methodology focuses on four key perspectives, which, when applied to warranty management, guide the establishment of targets and objectives to enhance program effectiveness.

1 Strategic formulation of the warranty program (as the possible externalization

[12] of warranty services or the development of warranty equipment with polyvalent technicians.

2 Translation of after-sales strategy to reachable short-term objectives (such as the identification of measures destined to push personnel to a global vision.

7.1 The Balanced Score Card in After-sales Management 119

3 Development of action plans (in order to reach the objectives identified in the previous step and taking into account the necessary changes in the business infrastructure of support).

Hierarchical Analysis in the Decision-Making

After defining the warranty program's objectives and strategies, it's essential to assess product criticality, which refers to the potential impact of customer claims on overall business strategy and outcomes Decisions made within the warranty program can lead to deviations from profit goals, resource reallocation, delays, or the use of assembly parts as spares Therefore, it is crucial to employ systematic techniques, such as risk-cost evaluation, to prioritize goods effectively in the warranty management process, aligning with the established strategy.

Table 7.1 Application of the BSC methodology to warranty management (adapted from [11])

To improve the effectiveness of warranty costs

Warranty costs per sold unit

To assure the correct acquisition of data and analysis of criticality of equipment

To improve repair time and service quality

Number of repetitive failures \ x Reduce the MTTR in a (Y) %

Failure analysis program and after-sales support improvement

Improvement in the service process and its documentation

In compliance with quality standards

Certification of services before a determined date

To develop procedures of pending technical inspections

To assure the correct levels of training to accomplish the mission

Level of training according to type of service

Definition of precise training levels

To carry out training and evaluation

The analysis of warranty issues combines the probability of events with their potential impact, resulting in a criticality matrix that prioritizes these events and aligns after-sales actions with company objectives This approach allows for efficient resource allocation, risk minimization, and reduced warranty costs, ultimately enhancing customer satisfaction By prioritizing customer complaints related to chronic failures, companies can quickly address the root causes of these issues, providing a significant advantage in warranty management The Analytic Hierarchy Process (AHP) aids in making strategic decisions by evaluating various factors such as price, weight, and customer satisfaction This method offers a realistic assessment of decisions while acknowledging minor inconsistencies inherent in subjective judgment.

7.2.1 General Features of the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP), developed by Thomas Saaty in 1970, simplifies complex decision-making by breaking problems into hierarchically ranked components This methodology quantifies and compares variables, synthesizing solutions through the geometric average of diverse perspectives AHP has proven valuable for corporate and government leaders in various decision-making scenarios, such as selecting telecommunication systems and formulating product marketing strategies.

The AHP method facilitates decision-making by breaking down problems into a structured hierarchy of criteria and alternatives Numerous studies have explored the application of the AHP method in decision-making processes The decision matrix synthesizes the decision maker's information, comparing criteria in pairs using a normalized and reciprocal scale to establish their relative importance.

7.2 Hierarchical Analysis in the Decision-Making Process During Warranty 121

The elements of decision matrix fulfill

• Reciprocity : w ij ẳ 1=w ji for all i; j ẳ 1; ; n:

• Consistency : w ij ẳ w ik =w jk for all i; j; k ẳ 1; ; n:

The method has the following axioms:

1 Reciprocity The importance of the relation W ij is the inverse of W ji , so W ii = 1.

2 Homogeneity Compared elements in relation to the same property have the same order of magnitude.

3 Dependence To control the dependence among the elements forms the same level and consecutive levels.

4 Performance of expectations The structure of criteria and alternatives has to represent the expectations in a ranking.

The application of this method allows for the incorporation of subjective values, which introduces a level of uncertainty and potential unreliability Therefore, it is essential to assess the sensitivity to changes in parameters To evaluate reliability (CR), we utilize the consistency ratio.

Alternative 2 Alternative … Alternative n CRITERION 1 CRITERION 2 CRITERION … CRITERION n

Fig 7.2 Problem decomposition into criteria and alternatives w 11 w 12 … w 1n w 21 w 22 … w 2n

3a67e368 0a4d3d50 cf8d5 f476 8201 e328 cbbba50 c741 ebd4f6 b2e1 0316e d218 e1d2 918 rate (CI) of a comparison array into pairs to the value of the same index of a comparison array into pairs randomly generated:

Reliability is considered adequate when the Composite Reliability (CR) is 0.10 or lower; if it exceeds this threshold, a review is necessary to enhance consistency Implementing this method in decision-making aims to achieve specific objectives.

• Improve organization, structuring, and documentation (feedback) of the process.

• Use a rational and logical analysis, which minimizes emotional burden of trials.

• Employ quantitative and qualitative criteria, accurate or measurable, and inac- curate or estimated.

• Consensus and satisfaction in group decision-making.

• Predict at times likely results.

The Analytical Hierarchy Process (AHP) has been utilized across various business contexts, as well as in political and personal decision-making scenarios, particularly when integrating insights from multiple experts is essential for informed choices.

1 Personal situations, where everything is looking on organizing and reflecting internal preferences, for example acquisition of resources and identification of tracks.

2 Political situations in public administrations Generally is orientated to consensus achievement or forecasting future, for example identification of public transport routes and public services allocation.

3 Business situations in private companies Orientated mainly by competitiveness and improvement, it is used in all situations to achieve objectives: organization, structuring projects, resource allocation, prediction, etc.

Table 7.2 Saaty scale to compare criteria in pairs

Saaty scale Reciprocal Saaty scale

1 Equal importance of both elements – –

3 Weak importance of one element over another

1/3 Slightly less importance of one over another

5 Essential or strong importance of one element over another

1/5 Less importance of one over another

7 Demonstrated and very strong importance of one element over another

1/7 Far less importance of one over another

9 Absolute importance of one element over another

1/9 Absolute less importance of one over another

1/6, 1/8Intermediate values7.2 Hierarchical Analysis in the Decision-Making Process During Warranty 123

In our case, AHP method is orientated to continuous improvement, having taken into account the following points [18–20]:

• If the number of alternatives grows, comparisons grow exponentially, and the use of method can be made cumbersome [21].

• It does not consider variation in criteria ranges.

• It is more a comparing tool for management than a statistical method [22].

• Valuations of comparisons can be interpreted differently by different subjects.

• Individually comparison may lead to conflicts, because if A [ B and B [ C, it may occur A \ C.

• Inclusion of a new irrelevant approach may affect management of two relevant criteria [23] This would contradict axiom of multi attribute value theory (MAVT) on irrelevant alternatives [24].

• Asymmetrical inconsistency in eigenvectors by Saaty scales [25, 26].

To correct this lack of consistency, the modified AHP method was developed

[25], Donegan et al [26], but also it has its criticisms [27], indicating that improvements in real cases are not as crucial as Saaty AHP original method.

Root Cause Analysis in Warranty Management

7.3.1 Root Cause Analysis for the Identification of Physical Causes

To enhance company benefits through improved maintenance and extended after-sales services, it is essential to increase equipment reliability and prolong the lifespan of physical assets and market products The primary goal of industrial asset management is to predict process alterations and detect unplanned production issues, thereby minimizing potential losses and maximizing profits Effective maintenance management and after-sales service strategies must align with the company's business plan to achieve these objectives Additionally, the integration of new technologies necessitates a skilled technical assistance team, capable of addressing both technical and managerial challenges This underscores the need for advanced tools that provide reliable solutions in after-sales services, while the adoption of targeted methodologies in maintenance can significantly lower costs by addressing the root causes of failures.

To effectively tackle maintenance challenges, it's essential to employ tools like Total Productive Maintenance (TPM) and Reliability-Centered Maintenance (RCM) RCM focuses on analyzing system functions and failures to identify consequences and implement preventative measures through standardized procedures However, it may not delve deeply into the underlying mechanisms of failure Proactive maintenance further utilizes tools such as Root Cause Failure Analysis (RCFA), Failure Modes and Effects Analysis (FMEA), Critical Analysis (CA), and Acceptance Testing and Age Exploration (AE) Some experts even categorize a subset of this approach as Radical Maintenance (RM), which emphasizes detecting and predicting root causes of failures to implement measures that eliminate these root causes or their contributing conditions.

There is a diverse range of tools and methods available for identifying the root causes of specific events or failures, each varying in complexity, information quality, and applicability The most commonly used methodologies include 5 Whys analysis, change analysis, current reality tree (CRT), Failure Modes and Effects Analysis (FMEA), fault tree analysis (FTA), Pareto analysis, Bayesian inference, and the Ishikawa diagram These methodologies can be categorized into qualitative methods, such as the 5 Whys and Ishikawa diagram, and quantitative methods, including Bayesian inference and Pareto analysis, highlighting their substantial differences and unique applications in root cause analysis.

Qualitative methodologies often involve brainstorming, while quantitative approaches may require complex mathematical techniques Utilizing root cause analysis (RCA) tools is crucial for maintenance and after-sales services, as it helps identify the primary causes of failures that can be influenced by management or operational decisions To prevent chronic and recurring failures, it is essential not only to pinpoint the origins of these issues but also to develop corrective and preventive action plans.

The use of specialized tools is crucial for effective maintenance strategies, particularly in providing temporary solutions for customers awaiting long-term repairs under warranty Implementing proactive maintenance, which arises from corrective actions, enhances organizational protection regarding warranty management Additionally, Bayesian networks facilitate decision-making through probabilistic reasoning, enabling the calculation of future event probabilities and adaptability to changes The goal of monitoring and diagnosis is to merge existing process knowledge with current physical evidence, leading to a more accurate understanding of process behavior Bayes' theorem further enriches this predictive support for diagnosis, as illustrated in the accompanying flowchart.

7.3 The Root Cause Analysis in Warranty Management 125

The article discusses the unique methodologies of Root Cause Analysis (RCA) within a staged maintenance management model, serving as the foundation for a warranty management program outlined in the previous chapter.

This chapter introduces the hierarchical analysis process, highlighting the role of Pareto analysis in identifying critical equipment alongside the criticality matrix The Failure Mode and Effects Analysis (FMEA) is utilized to assess weak points in critical equipment by evaluating causes, failure modes, and effects Additionally, the Cause Analysis (CA) determines the significance of these weak points on system performance For more complex evaluations of root causes and critical weaknesses, Event Tree Analysis (ETA) or Bayesian inference can be employed, aiding in the development of an effective action plan tailored to the after-sales and maintenance strategy It is crucial to note that the effectiveness of these methodologies relies on their proper application for specific contexts.

Fig 7.4 Location of the RCA methodologies focused on maintenance management

The requirement of a specific stage within a reference management framework encompasses its characteristics, information needs, and resources A root cause of failure is identified as the fundamental cause that can be reasonably recognized and managed Supporting literature indicates that there are three levels of root cause failure within a system.

• Physical Root Cause: Failure on equipment caused by physical reasons.

• Human Root Cause: Failure on equipment caused by human intervention.

• Latent Root Cause: Failure on equipment caused by decisions at an organizational level that leads to an event of failure.

Failure analysis (FA), also known as root cause analysis (RCA), involves a detailed examination of failed components to identify the underlying causes and enhance system reliability This structured approach utilizes specific techniques to effectively identify and resolve issues, targeting the root causes rather than merely addressing the symptoms of failures By implementing RCA, organizations can eliminate or reduce the factors that lead to recurring failures There are four distinct groups of RCA methods available for this process.

Following, there is a brief explanation of the most used RCA methodologies in reliability engineering, standing out their advantages and limitations These are

• Failure Modes and Effects Analysis:

Failure Mode and Effects Analysis (FMEA) and its Criticality Analysis (FMECA) are qualitative techniques used to identify potential failure modes and evaluate their impacts on systems and components These methods systematically examine failure modes at various levels, including components, equipment, and subsystems, assessing their effects and criticality while also determining the likelihood of occurrence By identifying potential failures, FMEA and FMECA propose strategies to mitigate or prevent adverse consequences, enhancing system reliability and performance.

Table 7.3 Classification of the RCA groups based on their focus Root Cause Analysis groups

The deductive approach utilizes general-to-specific reasoning, exemplified by failure tree analysis, while the inductive approach focuses on deriving general conclusions from individual cases, as seen in cause-and-effect diagrams and HAZOP analysis Both methodologies play crucial roles in systematic problem-solving and risk assessment.

The Morphological Method analyzes the structure of the studied system, emphasizing potentially dangerous elements It prioritizes factors that significantly impact system security, such as accident evolution, barriers, and workplace health and safety.

Concepts and techniques non-orientated to systems such as the previous ones (for example, analysis of change and study of probability of human error)

To ensure the reliability and security of system functions on a global scale, it's essential to identify areas needing improvement This method employs an inductive approach, beginning with a component's failure and examining its effects throughout the system to uncover all potential consequences However, it has limitations, particularly in complex scenarios, as it struggles to identify related causes beyond the specific failure mode analyzed Additionally, its effectiveness is influenced by the experience of the development team.

Fault Tree Analysis (FTA) is a deductive and quantitative method that investigates the causes of an undesirable event, referred to as the "superior event," while quantifying its probability of occurrence This analysis employs a logical diagram that illustrates the hierarchical relationships between various elemental events leading to the superior event The tree-like graphical representation allows for the identification and classification of potential failure events within a system, facilitating the estimation of failure probabilities FTA is favored for its user-friendly nature and its high level of intuitive abstraction, utilizing conventional logical symbols to clearly depict causal relationships.

The Fault Tree Analysis (FTA) enhances system security and reliability by focusing on specific combinations of events, such as "Y" and "O." It aids in predicting potential failures by detailing the conditions under which they may arise and assessing the significance of critical system elements This technique is applicable to both static and dynamic complex systems, providing a solid foundation for analyzing system design, common failures, and ensuring compliance with security requirements While FTA offers valuable insights, it has limitations as a root cause analysis (RCA) tool, particularly in managing functional dependencies between components, and it relies on specific information about known failure causes Despite these challenges, it is often utilized to support RCA efforts.

• Cause-and-Effect Diagram (CED):

Case Study on Balanced Score Card

This practical example is based also on the case that will be described in Chap 13, which deals with a manufacturing company that also assembles farm machinery

This article applies the principles of the balanced scorecard to a company focused on the production, sales, and repair of harvest machinery and its heads, both new and used A crucial strategy for the company is to enhance its technical support services, specifically by optimizing after-sales processes to boost profitability and ensure customer retention for future sales Key after-sales activities include providing spare parts, warranty services, and maintenance contracts to customers.

The company's management aims to analyze the financial efficiency of four key business aspects: the sale of new and secondhand harvesters and their respective harvest heads, focusing on warranty costs This comprehensive evaluation will enable the company to realign objectives and enhance customer service across all products, identifying which items yield the highest and lowest benefits Additionally, addressing the potential losses incurred from a harvester's inactivity is crucial for customer satisfaction.

Therefore, during harvest season, these machines should be at their highest performance capacities, and in the event of a breakdown, a quick repair should be

The parent company or authorized assistance centers guarantee technical support, necessitating a strategic shift to minimize unexpected repair interventions, particularly during the harvest season, when such issues are challenging to manage.

To effectively monitor performance, the company needs to establish key performance indicators (KPIs) such as the product's sales price, warranty costs, and their percentage relative to the sales price Additionally, clear objectives for both percentage and monetary values regarding warranty costs must be defined Detailed information for each product type can be found in Tables 7.5, 7.6, 7.7, and 7.8, categorized by machine type.

When evaluating the prices of new or secondhand attachments, it is essential to focus solely on the cost of the harvest heads, using an estimated base price of €180,000 for the machine itself The data presented in this case study is organized by projects, reflecting a potential trend of improving manufacturing processes over time, which may lead to a reduction in issues arising during the warranty period.

Maintenance encompasses actions that manage the deterioration process to prevent system failures (preventive maintenance) and restore a system to its operational state through corrective measures following a failure (corrective maintenance).

Clear communication between manufacturers and customers is essential when providing warranty assistance, as both parties need to understand the service details and the conditions for assistance In the farm machinery sector, whether dealing with new or used equipment, there are opportunities for maintenance contracts and warranty extensions While this article does not focus on that topic, it suggests that evaluating the impact of preventive maintenance contracts on after-sales performance using the balanced scorecard methodology could be a valuable area for future research.

In other words, carry out this case study from three different scenarios (as it will be mentioned in Chap 13):

• Scenario A: No preventive maintenance contracts are applied, neither under the warranty period nor not.

• Scenario B: Users hire preventive maintenance services only during the warranty period.

• Scenario C: Users hire preventive maintenance services not only during the warranty period but also once it expires throughout the product’s life cycle.

This case study focuses solely on warranty costs in scenario A, highlighting that the findings may vary if the impact of maintenance hire is taken into account.

Table 7.5 presents key performance indicators (KPIs) for the Harvesters Model 554 project, detailing machine sales prices, warranty amounts, and their respective percentages relative to sales prices The warranty percentages range from 0.0% to 2.6%, with an objective improvement target of 1.8% across all models Notable sales prices include PF 129 at €190,790 and PF 130 at €191,000, both with warranty percentages at 0.0% The warranty objective is consistently set at €3,600, with potential improvements varying from €3,240 to €3,600, indicating areas for enhancement in warranty performance.

7.4 Case Study on Balanced Score Card 135

Table 7.6 presents key performance indicators (KPIs) related to the harvest heads model LM Proyec, detailing machine sales prices, warranty amounts, and their respective percentages The machines listed include MC 00 LM 600 with a sales price of €55,524 and a warranty of €4,678 (8.4%), and MC 01 LM 500 priced at €67,000 with a warranty of €2,581 (3.9%) Other models, such as MC 02 D225+LM600 and MC 03 D210+LM600, show warranties of €5,279 (2.6%) and €978 (1.7%), respectively The MC 04 DX180+LM500 has a sales price of €215,000 but a low warranty of €190 (0.5%) The MC 05 LM 600 and MC 06 LM 500 have warranties of €947 (1.3%) and €1,396 (2.4%), respectively The target warranty percentage across all models is set at 2%, with improvement objectives aiming for a consistent warranty target of €1,200.

7.4.2 Results in the Practical Application

Following our particular case, in Fig 7.6, four graphics can be observed as the result of the previous tables.

Graphics in Fig 7.6 represent the following values:

• Percentage values of the warranty cost in terms to the sales price, dots in the form of rhombus and colored in dark gray;

• The tendency of the warranty, continuous line in light gray;

• The objective value, dash and dot line;

• And the ‘‘challenge’’ or proposed improvement in the objective, gray dotted line.

The graphics illustrate warranty cost trends relative to sales prices, with an upward trend for used harvesters and a downward or oscillating trend for harvest heads LM Products with rising warranty cost tendencies are indicated by a dark gray triangle, while those with decreasing trends are marked by a light gray rectangle Additionally, products with mean warranty costs exceeding the target value are highlighted for emphasis.

Table 7.8 KPI relative to used headings Project Machine Sales price

Improvement obj % warranty/ sales price

Table 7.7 KPI relative to used harvesters Project Machine Sales price

Improvement obj % warranty/ sales price

7.4 Case Study on Balanced Score Card 137

The analysis reveals that the sales of the LM harvest heads model demonstrate inadequate after-sales service performance from a financial perspective, while the Model 554 harvesters show contrasting results Additionally, sales of used harvesters, despite meeting warranty cost objectives, are projected to see a rise in after-sales service costs, surpassing target values in the near future These trends indicate significant implications for decision-making, including personnel restructuring and equipment updates The Balanced Scorecard (BSC) methodology effectively identifies these issues, enabling proactive management discussions and foresight into potential challenges For further insights, references on the balanced scorecard and financial perspectives are available.

Coste medio de garantía / Precio de venta

Coste medio de garantía / Precio de venta COSTS DE GARANTÍA POR PROYECTO COSTS DE GARANTÍA POR PROYECTO

COSTS DE GARANTÍA POR PROYECTO COSTS DE GARANTÍA POR PROYECTO

COSECHADORAS MODELO 554 CABEZALES MODELO LM

Coste medio de garantía / Precio de venta Coste medio de garantía / Precio de venta

OP 02 OP 09 OP 36 OP 51 OP 63 OP 67 OP 70 OP 72

OP 66 OP 10 OP 15 OP 18 OP 21 OP 25 OP 27 OP 35

PF 102 PF 114 PF 116 PF 118 PF 120 PF 122 PF 125 PF 129 PF 131 PF 133

MC 00 MC 01 MC 02 MC 03 MC 04 MC 05 MC 06

Case Study on an Analytic Hierarchy Process

In Chap 3, a scenario was described on which the present case study will be based.

To apply the AHP methodology discussed earlier, we will follow a straightforward process consisting of three key steps.

1 State the objective: to obtain a spare part for the warranty assistance with minimal effects on the assembly line.

• Criterion 1: Stock extra (the higher the extra stock the better).

• Criterion 2: Terms – Criterion 2.1: Supply term (the shorter the supply time the better).

– Criterion 2.2: Repair term (the shorter the repair time the better).

• Criterion 3: Reliability (the higher is the reliability, or lower is the failure frequency, the better).

• Criterion 4: Costs – Criterion 4.1: Supply cost (the lower is the supply cost the better).

– Criterion 4.2: Repair cost (the lower is the repair cost the better).

• Criterion 5: Vehicles amount – Criterion 5.1: vehicles still to deliver (the higher is the amount of vehicles to deliver the better).

– Criterion 5.2: vehicles under warranty (the lower is the amount of vehicles under warranty the better).

• Spare part is obtained from warehouse.

• Spare part is obtained by cannibalization.

• Spare part is obtained by purchasing.

This information can be arranged in a hierarchical tree or in a chart In any case, the information is then synthesized to determine relative rankings of alternatives.

Informed judgments can be utilized to compare both qualitative and quantitative criteria, allowing for the determination of weights and priorities This process involves assessing the relative importance of each criterion through pairwise comparisons, which categorize their significance on a scale from 1 (equal importance) to 9 (extreme importance) By applying this method, as demonstrated by Dr Thomas L Saaty, a ranking of priorities can be derived from the pairwise comparison matrix, facilitating a clearer understanding of the criteria's relative importance.

7.5 Case Study on an Analytic Hierarchy Process 139

The eigenvector solution is considered the most effective method for analysis To compute the eigenvector, a straightforward approach involves raising the pairwise matrix to successive powers, squaring each time, and then calculating the sum of each row followed by normalization.

The process concludes when the difference between the sums of two consecutive calculations falls below a specified threshold The resulting eigenvector provides the relative ranking of the criteria (refer to Table 7.10) To assess consistency, we utilize the previously mentioned formulas for the Consistency Index (CI) and Consistency Ratio (CR) in relation to the maximum eigenvalue (k max), derived from the eigenvalues and the normalized pairwise comparison matrix (see Table 7.9).

The Consistency Index (CI) Rando value is influenced by the number of criteria being evaluated, with eight criteria being considered in this instance To assess consistency, Saaty introduced the Random Consistency Index (RCI), which involves generating reciprocal matrices using a scale of 1/9 to 9 By applying this method, similar to the bootstrap approach, a random consistency index is obtained to verify if it falls within the acceptable 10% threshold or less.

In terms of the alternatives, a pairwise comparison determines the preference of each alternative over another (see Table 7.12).

Table 7.9 Matrix of pairwise comparisons

AHP effectively integrates both qualitative and quantitative data, and in our case study, we have focused on a qualitative perspective to outline a general context.

• A high extra stock, reliability, as well as a high amount of vehicles still to be delivered;

• A short term in the supply and/or the repair of a piece; and

• A low cost in the supply and/or the repair of a piece, as well as a low amount of vehicles under warranty.

With the previously mentioned context, computing the eigenvector will determine the relative ranking of alternatives under each criterion (see Table 7.13).

Multiplying in terms of eigenvalues, the relative ranking of alternatives and the relative ranking of criteria, we can obtain the highest ranked alternative under the described context (Tables 7.14, 7.15, 7.16).

In the given context, the optimal choice is to source spare parts from the warehouse, while cannibalization serves as a secondary option for the manager The least favorable decision is to purchase the spare parts Overall, the Analytic Hierarchy Process (AHP) offers a structured approach to evaluate the advantages of each alternative, allowing for additional insights from the numerical outcomes.

The executive manager can utilize this tool for sensitivity analysis to assess the impact of decisions, such as purchasing additional units or repairing a failed component This analysis reveals how changes in key assumptions—like extra stock, supply terms, and costs—can affect decision-making outcomes Ultimately, it provides valuable insights into the critical factors influencing the issue at hand.

Table 7.10 Ranking of defined criteria

Table 7.11 Random consistency index (RCI)

Table 7.12 presents the eigenvalues for various alternatives, including Warehouse, Cannibalization, and Purchasing, across different criteria such as extra stock, supply cost, repair cost, vehicles still to deliver, and reliability The analysis reveals that the Warehouse option consistently scores high, particularly with an eigenvalue of 3.0000 for both supply cost and repair cost, indicating its strong performance Cannibalization shows varying results, with eigenvalues of 2.0000 for supply cost and 3.0000 for vehicles still to deliver, suggesting its competitive edge in certain areas Meanwhile, Purchasing demonstrates lower eigenvalues, notably 1.0000 for reliability, highlighting its limitations compared to the other alternatives Overall, the findings underscore the importance of evaluating these alternatives based on their eigenvalues to inform strategic decisions in inventory management and resource allocation.

In evaluating alternatives based on various criteria for obtaining spare parts, Warehouse ranks highest across multiple factors, including supply cost and reliability Cannibalization follows closely, excelling in repair term and reliability, while Purchasing ranks lower overall The optimal scenario for each criterion highlights the importance of prioritizing high reliability and short supply and repair terms, alongside managing costs effectively.

In complex decision-making, it's often beneficial to evaluate the advantages of alternatives before considering costs Focusing on costs prematurely may lead to overlooking the potential benefits of a warranty program, which could result in perceiving the overall expenses as excessively high Additionally, discussing costs alongside benefits can evoke political and emotional responses, complicating the decision-making process.

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Table 7.15 Eigenvalues according to criteria (matrix 2) Criteria Eigenvalues

Table 7.16 Result of the alternative ranking Warehouse 0.4117

Table 7.14 Eigenvalues according to alternatives (matrix 1)

Vehicles under warranty Warehouse 0.5936 0.2493 0.2493 0.2493 0.1571 0.5936 0.5936 0.5936 Cannibalization 0.2493 0.1571 0.5936 0.5936 0.2493 0.2493 0.2493 0.1571 Purchasing 0.1571 0.5936 0.1571 0.1571 0.5936 0.1571 0.1571 0.2493

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Reliability Engineering and System Safety Pp 287-300.

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Computers and Chemical Engineering Pp 244-253.

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The Logistic Support in the Technical Assistance

This section will explore the critical role of logistic support in warranty management, addressing key issues that influence the effectiveness of warranty processes.

1 The classification of elements’ candidates for a logistic support analysis (i.e., those components of the industrial asset, which, due to its importance according to certain factors, deserve to be especially analyzed for the warranty management).

2 The choice of repair echelons (i.e., those levels where it is more efficient to perform the assistance, in order to take appropriate measures for the development of a warranty program).

3 The definition of tasks (i.e., methods that define maintenance and warranty tasks for a component of a specific product).

To successfully introduce a new product with an appropriate warranty program, it is essential to identify and evaluate the logistic support during the initial stages of its product life cycle Existing references and standards primarily address this topic, particularly within the military sector.

According to these references, the data required for a logistics support analysis can be categorized under three different groups:

• Data related to product configuration and its requirements;

• Data related to possible failures; and

• Data related to maintenance and components acquisition.

Logistic support analysis is a vital iterative process for company management, enabling them to effectively size the customer service department, assess staff qualifications, and determine necessary materials This analysis aims to ensure that appropriate technical assistance is provided to customers throughout the product warranty period.

The following chart (Table 8.1) shows the interaction with other disciplines and how logistic support can influence them.

This table highlights non-traditional elements of logistic support, such as reliability, maintenance, design, and standardization, which, while not typically classified as logistical components, play a crucial role in the overall process The evaluation of products from a logistic support perspective involves analyzing parts, types, quantities, technical requirements, technician skill levels, tools, and documentation necessary for operation and repair Ultimately, these factors are essential for developing a technical assistance program that ensures a strong product-market position.

It will therefore be necessary a database that records those sources of logistic support as well as the identification and acquisition of elements.

8.1.1 Classification of Elements Candidates for a Logistic Support Analysis

Those logistic support candidates to be considered in a logistic support analysis process [1, 4] can be defined as follows:

• Logistic Support Full Candidate: Components requiring that their logistic support is fully analyzed (fiability, maintainability, disponibility, required skills, tools, manpower, etc.).

Logistic Support Administrative Candidates are essential components that, while not requiring a thorough logistic support analysis, play a crucial role in the overall evaluation of full candidates Essentially, these administrative candidates must be managed effectively to facilitate access to other product candidates.

Table 8.1 Logistic support influence Disciplines or areas Logistic support influence

1 Reliability and maintenance LORA, FMECA, RCM/failure rates/MTTR, MTBM

3 Manpower/technicians Required skills/staff knowledge

5 Tools and equipments Special tools/test equipments

6 Technical documentation Catalog of spare parts/maintenance manuals

7 Simulation and training Staff skills

8 Computer-based support Hardware/software reliability

9 Facilities Required equipments and location

10 Transport/dimensions Mass, size, weight/volume, transport, type

A flowchart in Fig 8.1 outlines a procedure for selecting candidates for logistic support, emphasizing the importance of understanding key elements for effective maintenance and warranty planning The first critical factor is component reliability, where components with high failure rates are prioritized for inclusion in the logistic support candidate list To refine this list, threshold limits for failure rates can be established based on operational metrics The second factor is maintenance, focusing on components that necessitate intensive preventive maintenance, specialized staff training, or exhibit high technical complexity Candidates must also include components requiring scheduled preventive maintenance to ensure optimal system performance throughout its lifecycle The third factor involves the need for support equipment or special tools for both preventive and corrective maintenance tasks Lastly, the criticality of components is considered, where candidates include those whose failure poses safety risks to the product or user, thereby impacting the product's functionality.

There are four standardized levels to measure the criticality:

1 Catastrophic: failure can cause the loss of the entire system.

2 Critical: failure can cause serious damage to the system, so the product cannot achieve the success of its functions.

3 Marginal: failure can cause damage to the system, so there is a delay or loss of product availability.

4 Minor: failure is not serious enough to cause damage to the system, but an unscheduled repair will probably be required.

The fifth factor to consider is the accessibility of components A component may qualify as an administrative candidate if it needs to be removed to access other full product candidates or if frequent access is required Ultimately, if a component does not meet these criteria, it will be classified as a non-candidate.

After selecting logistic support candidates, a Level of Repair Analysis (LORA) should be conducted, as the chosen repair level significantly impacts cost-effectiveness in logistic support The primary goal of this analysis is to determine the most appropriate actions during the development phase.

8.1 The Logistic Support in the Technical Assistance 149

Fig 8.1 Procedure to select logistic support candidates

The proposed framework evaluates maintenance and warranty tasks throughout a product's lifecycle, aiming to minimize costs It utilizes repair levels derived from the military sector, including line repairable units (LRUs) and shop repairable units (SRUs), to determine optimal maintenance echelons By calculating repair costs at various levels (C1, C2, C3, and C4) based on direct labor, materials, and handling, the framework identifies the most cost-effective echelon for repairs Additionally, it may consider a fifth echelon for significant reconstructions and overhauls conducted by industrial maintenance.

Future research in this field should explore the calculation of various costs not covered in this study and investigate the potential integration of extended warranties with maintenance assistance after the warranty period ends.

In literature, various methods are outlined for defining maintenance and warranty tasks related to product component failures A key approach is the failure modes, effects, and criticality analysis (FMECA), which effectively identifies necessary maintenance tasks and their application to warranty assistance In the context of warranty management, reliability-centered maintenance (RCM) serves as a dependability analysis to establish the tasks to be performed during the warranty period, based on anticipated customer complaints.

Table 8.2 Repair levels (adapted from [5]) Repair level

Echelon 1 Developed by the user C 1

Preventive maintenance tasks by the operator

Echelon 2 General changes for parts and adjustments C 2

Preventive tasks and correction (e.g., duration 4 man/hour) Echelon 3 In-place repair/change of damaged assemblies C 3

Preventive tasks and correction (e.g., 4 man/hour \ duration 50 man/hour)

Echelon 4 General repair of damaged sets and subsets C 4

Preventive tasks and correction, determined by maintenance manuals when duration [ 50 man/hour

8.1 The Logistic Support in the Technical Assistance 151

In assessing the criticality of failure modes in various technologies, the safety hazard severity code (SHSC) categorizes failures as catastrophic, critical, marginal, or minor Alternatively, a more quantitative assessment is often employed, particularly in the military sector.

C m ð ị n where n ẳ 1; ; N where [8] is as follows:

• C m (modal criticality number): It is calculated for each failure mode of each logistic support item.

• C r (item criticality number): It is calculated for each logistic support item.

• k p (failure rate): It is usually obtained from failure rate predictions [9, 10].

• a (failure mode rate): It is usually obtained from failure mode database sources such as [11].

• b (conditional probability): It is the analyst’s best judgment that the failure will occur, based on the item severity classification.

• t (mission phase duration): In military or aerospace sectors, it is an average data of the usual system functioning.

Product analysis is essential for identifying preventive tasks necessary for effective warranty management The findings from FMECA and RCM can be applied to enhance technical assistance in warranty programs Future research could explore the integration of RCM and FMECA with customer relationship management (CRM), a key component in the proposed warranty management framework This integration, often referred to as reliability-centered maintenance and optimization (RCMO), can lead to improved customer service strategies and enhance the efficiency of warranty management, ultimately boosting customer satisfaction After identifying the tasks for the warranty period and potential extensions or maintenance contracts, it is crucial to establish the frequency of these tasks This frequency is typically determined by product engineering experience and forecasts of potential customer claims based on product reliability, often calculated using specific formulations.

TF ẳ ð 1=MTBF tec ỵ 1=MTBM in ỵ 1=MTBM nd ị AOR where

MTBF tec Mean Time Between Failure Technical MTBM in Mean Time Between Maintenance Induced MTBM nd Mean Time Between Maintenance No Defect AOR Annual Operating Requirements

In order to obtain an in-depth knowledge on this formula, we suggest consulting the Ref [1], which defines the parameters for calculating the frequency However, simplifying:

Mean Time Between Technical Failures (MTBF tec) is a key indicator of system reliability, derived from the known failure rates of various components and supported by documented technical characteristics This metric reflects the necessary technical reliability that the system or equipment must achieve In establishing these parameter values, all failures and the subsequent actions taken to restore the system are thoroughly considered.

Practical Case on Customer Risk

This chapter and Chapter 10 highlight two critical aspects of warranty management: risk analysis for enhancing after-sales management and customer relations management Typically, warranties are associated with physical products sold for use over an expected lifespan Customer dissatisfaction can lead to product abandonment, dissatisfaction during use, or resale in the secondhand market, complicating the assessment of dissatisfaction costs However, not all market offerings are tangible products; some services, like water, gas, and energy distribution, also require guaranteed utility For instance, a water-distribution campaign operates through a hierarchical network to serve customers, exhibiting distinct characteristics compared to traditional manufacturers.

• Geographical distribution with variable environmental conditions.

• High number and different types of elements.

• High number and different types of clients.

• Elements are interrelated among themselves.

Table 8.5 Chart about CPI and SPI meaning

CPI Under the budget Over the budget

SPI Ahead of schedule Behind the schedule

8.2 Costs-Risks–Benefits Analysis in the After-sales Management 165

• Hierarchical structure in the element network with different levels of customer service.

• The infrastructure experiences operational and configuration changes.

• High level of demand in the human resources and material (replacements).

In companies that prioritize customer satisfaction, assessing levels of dissatisfaction is straightforward, as customers can easily switch to competitors if their needs are not met This necessitates a thorough understanding of potential service incidents and their impact on quality Warranty and maintenance services must effectively identify, analyze, and mitigate risks to ensure customer satisfaction Future research could explore various statistical methods to evaluate these risks It's crucial to measure poor quality in terms of costs, linking quality evolution directly to customer satisfaction While preventive costs are predictable, failure costs can vary, with some being quantifiable and others intangible To achieve efficient warranty management, businesses must analyze factors such as the severity of incidents, corrective actions, preventive measures, and associated budgets, focusing on the most significant risks from both business and customer perspectives.

• Customer relations: loyalty decrease due to poor and deficient customer service.

• Price and quality: bad-service disposition increases costs and contributes to customer dissatisfaction.

• Internal personnel motivation, image and external prestige of the company.

In short, this analysis is focused on the intangible costs’ impact on the customer when dealing with failures and their consequences on the company.

Fig 8.7 Infrastructure of a distribution company

• Loss of image and customers.

Owing to the fact that costs are intangible, they will have to be estimated with hypothetical and statistical criteria.

8.3.2 Initial Hypotheses and Quantification of Consequences

In order to show the effect of poor quality, we will take into account three hypotheses:

1 The effect of poor quality on the customer will be based on previously carried out studies regarding this issue [41], in which customer reclamations in more than 400 big service companies in the USA, Japan, and Europe concluded that a dissatisfied customer transmits his own bad experience to an average of 9–10 potential customers, and on the other hand, only a 17 % of dissatisfied customers had the intention to continue with the services provided by the company in question.

2 To assess the relation between customers and businesses, we will use the variable ‘‘customer net present value’’ (CNPV) The CNPV variable will be the updated benefit per client In other words, it corresponds to the total of obtained income from a client during its relation with the company, minus the direct costs of sales, acquisition, and customer loyalty.

3 As a third hypothesis, there is a certain probability that a dissatisfied customer will abandon the service This probability will be estimated using warranty and maintenance indicators from statistical and analytical methods (‘‘service level of agreements (SLA)’’) These methods analyze the behavior of a group of customers that suffer a failure at a point after a certain period of time [42].

To evaluate the impact of the service on the warranty in terms of costs, we will use the following equation [43]:

Risks ðRị ẳ Rðprobability of occurrence consequence costsị i ẳ 1; ; n ð8:1ị

Along all this, intangible costs of loss of production, customer and corporative image, as well as risk assessment are described as follows:

Service interruptions lead to profit losses by decreasing the Customer Net Present Value (CNPV) for each client To enhance customer retention and prolong service contracts, it is essential to minimize production losses associated with service failures This can be achieved by calculating the downtime (T r) from the moment a failure occurs until it is repaired Consequently, even a single service failure can result in significant financial losses.

8.3 Practical Case on Customer Risk 167

The LP represents the percentage of time a company must apply discounts to the CNPV for each client, utilizing an average CNPV value in the calculation Additionally, the evaluation period should be established, reflecting the average duration of customer retention within the company (Tc).

The value m i is the number of affected customers per individual failure (i = 1,

…, n) Obviously, the higher the hierarchical position of the device in the network, the more significant benefit losses are This is because the number of affected clients is greater.

(b) Customer and corporate image losses

Losses in terms of corporate image are due to bad publicity from a customer’s point of view, and it can be classified into three types of possible consequences:

• The company is losing customers.

• The company must reward customer loyalty.

• The company will have to pay more in order to attract more customers.

In other words, these consequences could be translated into a combination of Eqs (8.3), (8.4) and (8.5) Some parameters are needed for its deduction:

• p = expected number of people, customers and potential customers that are not directly affected by a failure but just influenced by bad publicity;

• r p = customers in a part of the population within a geographic area in the network;

• r po = expected proportion of customers as a business’ goal in a part of the population within a geographic area in the network;

• s c = ratio of gaining dissatisfied or influenced customers.

Quantifying certain parameters can be challenging, particularly when it comes to customer recovery costs The variable s l represents the discount or compensation offered to clients following unsatisfactory service, while s p denotes the marketing expenses incurred per client Additionally, s c refers to the investment made to attract new customers These three costs illustrate distinct customer behaviors, as outlined in the accompanying equations.

1 Customers can discard the service; therefore, the company loses net value per client and per year.

2 Customers continue with the service, but an s l to ensure customer loyalty is required.

3 A potential customer is influenced by bad recommendation In order to compensate for this, more publicity is needed.

Therefore, these three above-mentioned costs use estimations for the comment:

CLC is the sum of CNPV per every lost customer, multiplied by the customer abandonment probability As follows:

Equation (8.3) includes abandonment probability of a customer (affected by a failure), and the abandonment probability of others due to a bad experience passed on by the affected customer.

In the same way, the CLY costs are calculated as the loyalty costs of influenced customers:

Equation (8.4) combines the likelihood of retaining an affected customer with the risk of losing others due to the negative experience shared by that customer Similar to Equation (8.3), it is important to note that not all individuals influenced by this experience are customers; only a subset of them, represented by r p, are directly impacted.

(b3) Capturing new customers cost (CCC):

In this case the equation is:

CCC ẳ P a ðs p ỵ s c ị 1 ỵ p ẵr p ỵ ẵr po r p ẳ P a ðs p ỵ s c ị 1 ỵ p r po ð8:5ị

This equation accounts for the costs associated with losing clients due to service failures and negative experiences shared by existing clients, represented by the probability of abandonment (r p) Additionally, the difference (r po - r p) reflects the potential clients that can be acquired by successfully meeting business objectives.

The study of abandonment probability related to service restoration time focuses on customers who endure a failure, utilizing survival analysis techniques By understanding the number of clients per network equipment, we can prioritize warranty tasks based on customer risk, aiming to minimize these risks more efficiently Utilizing the Weibull distribution, we can derive an equation that represents the probability of customer abandonment through a density probability function.

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d f ðt f ị ẳ b t b1 i a b

To determine the parameters a and b for analyzing customer abandonment times, it is recommended to utilize the logarithm of the credibility function K (Eq 8.7) This approach involves starting with a dataset that includes various abandonment times, denoted as t i.

K ẳ log L t f 1 ; t 2 ; ; t N ja b g ẳ X N iẳ1 log f ðt i j a bị ẳ X N iẳ1 ðln b b ln aị ỵ ðb 1ị ln ð ị t i t i a b ð8:7ị

In order to find the maximum, partial derivatives to the credibility logarithm are applied (Eqs 8.8 and 8.9). o log L oa ẳ X N iẳ1

1 b þ ln t i a 1 t i a b ẳ 0 ð8:8ị o log L ob ẳ n b a þ b a bþ1 X N iẳ1 t b i ẳ 0 ð8:9ị

Calculating future cost behavior often involves complex statistical methods, such as the Newton–Raphson technique, to ensure rapid convergence The primary objective is to derive equations that can predict costs based on market hypotheses and parameters, which must be connected to a probability framework This section presents results related to 30 equipment failures affecting approximately 250 clients, detailing each failure alongside the number of surviving customers (S) and the time until customer loss (F), as illustrated in Table 8.6.

The formulas developed previously have been utilized in a case study involving a water-distributing company, akin to the upcoming analysis in Chapter 11 Table 8.6 presents the relevant data in accordance with specific restrictions.

• p = 10, the expected number of people, customers and potential customers, influenced by bad publicity;

• r p = 0.33, relation of customers in a part of the population within a geographical area of the network;

• r po = 0.66, expected proportion of customers, as a target of the company within a geographical area of the network;

• s l = 25€, as the quota to retain customer fidelity,

• s p = 25€, as the quota for customer publicity,

• s c = 300€, as the quota for gaining an dissatisfied or influenced customer,

• T c = 21,000 h, the average life span of the customer in the company,

Table 8.6 List of lost and retained clients according to repair time Customers Status F or

The article outlines the significance of various columns in customer data analysis: "customers" indicates the number of customers within specific subsets; "status F or S" denotes whether customers are lost (F) or retained (S) following a failure; "Final status time" represents the timeframe in which customers choose to stay with or leave the service; and "ID of the subset" identifies the malfunctioning device associated with each customer.

General Characteristics of a RAMS Analysis

Next we are going to get the RAMS variables for two subsystems arranged in series or in parallel and for the case of a system formed by ‘‘n’’ identical

In systems configured with multiple subsystems operating in parallel, a failure occurs when "m" or more subsystems fail, known as the "m-out-of-n" case This scenario allows for the analysis of key system characteristics, including the ratio of system failure, mean time between failures, system availability and unavailability, and mean downtime It is important to recognize that traditional formulas may not always apply to hybrid configurations, necessitating the use of alternative methods such as probabilistic formulations for accurate assessment.

This section describes a system conformed by two nonidentical subsystems arranged in series (Fig 9.1).

The failure rate of a single subsystem is denoted as k1, with a corresponding probability of failure over a time interval dt being k1 dt In a series configuration with two subsystems, the probability of failure during dt combines to (k1 dt + k2 dt) Consequently, the overall failure rate for the system in series can be expressed as k series = k1 + k2.

The reliability function (assuming an exponential distribution) will be:

• Mean Time Between Failures Considering an exponential function for reliability, it follows that:

In order to make the system available, each subsystem must be available.

On the contrary, the unavailability will be:

UA series ẳ 1 A series ẳ 1 ð1 UA 1 ị ð1 UA 2 ị ẳ UA 1 ỵ UA 2 UA 1 UA 2

When analyzing two repairable subsystems with Mean Down Times (MDT) of MDT 1 and MDT 2, the mean downtime for the series configuration of these subsystems can be determined by assessing the system's four possible states at any given time Each state reflects the operational status of the subsystems, influencing the overall downtime experienced by the system Understanding these dynamics is crucial for optimizing maintenance strategies and minimizing operational interruptions.

176 9 On the Assessment and Control

– Subsystem #1 does not work, but #2 does.

– Subsystem #2 does not work, but #1 does.

– None of the two subsystems work.

The last three cases are critical, as their failure renders the entire system inoperable For an inactive system, the likelihood of inactivity caused by a failure in subsystem #1 is represented as k1 = (k1 + k2).

Since subsystem #1 needs a MDT 1 to be repaired, the repair time associated with this subsystem is then: k 1 = ð k 1 ỵ k 2 ị MDT 1

A similar expression is applied to the case of subsystem #2 Synthesizing both for the complete system, it is obtained as follows:

MDT series ẳ MTBF 1 MDT 2 ỵ MTBF 2 MDT 1

This section describes a system of two nonidentical subsystems arranged in parallel (Fig 9.2).

Here, the two subsystems are repairable, with downtime MDT 1 and MDT 2

If only subsystem #1 is operational, the complete system failure ratio is k1, resulting in a failure probability of k1 dt over a differential time dt However, when subsystem #2 is added in parallel, the system's failure probability in dt is reduced by the likelihood of subsystem #2 being in failure mode The probability of subsystem #2 being in failure mode is determined by specific criteria.

The reduced failure rates for subsystems #1 and #2 can be calculated using the Mean Down Time (MDT) and Mean Time Between Failures (MTBF) values Specifically, the reduced failure rate for subsystem #1 is given by k1/k2 * MDT2, while for subsystem #2, the formula is similarly applied.

Fig 9.1 Subsystems in series connection

9.1 General Characteristics of a RAMS Analysis 177

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d k 1 k 2 MDT 1

• Mean Time Between Failures Considering the approach that the inverse of the failure ratio is MTBF (certain for an exponential distribution), we obtain:

MTBF parallel ẳ 1=k parallel ẳ MTBF 1 MTBF 2

Note that if the two subsystems are not repairable, then the MTBF for the case in parallel is the sum of the individual MTBFs.

• Availability and Unavailability For the system becomes available, any of the subsystems should be available.

On the contrary, the unavailability will be:

UA parallel ẳ 1 A parallel ẳ 1 ð A 1 ỵ A 2 A 1 A 2 ị ẳ ð 1 A 1 ị ð 1 A 2 ị ẳ UA 1 UA 2 ð9:1ị

MTBF The MDT may be obtained for the case in parallel, using expression (9.1) above.

Fig 9.2 Subsystems in parallel connection

9.1.3 Case of n Identical Subsystems in Parallel

In a system comprising n identical subsystems, the entire system experiences failure when m or more subsystems fail This scenario necessitates specific formulas to calculate the failure rate, mean time between failures (MTBF), availability, and downtime for the overall system.

In a system comprising solely of subsystem #1, the failure rate is represented by k, leading to a failure probability of kdt over a time interval dt For a complete system failure, it is necessary for (m - 1) additional subsystems to also be in failure mode The likelihood of any subsystem being in failure mode can be expressed as MDT/(MTBF + MDT), or simplified to MDT/MTBF under the assumption that MDT is less than MTBF To determine the probability of (m - 1) subsystems failing, the relevant calculations must be performed.

There will be n1 C m1 ways for the group (m - 1) out of the (n - 1) subsystems.

In addition to this, any subsystem can be selected to be analyzed as subsystem #1.

Considering all together we obtain: k moutofn ẳ k MDT

MTBF m1 n1 C m1 n ẳ n! ðn mị!ðm 1ị! k m MDT m1 ð9:2ị

The failure rate for exactly m failed subsystems indicates that when the number of failed subsystems exceeds m, the failure rate decreases by a factor of ðk MDTị For a consistent analysis, consider the case where n = m = 2, representing two identical subsystems in parallel In this scenario, if both subsystems fail, the entire system fails The corresponding expression is k system ẳ k 2 ð2 MDTị, which aligns with the formula from the previous section for two parallel-connected subsystems.

• Mean Time Between Failures Considering the approach that the inverse of the failure rate is the MBTF (indeed, as mentioned above, certain for an exponential distribution), we obtain:

MTBF moutofn ẳ 1=k moutofn ẳ MTBF m n! ðnmị!ðm1ị! MDT m1

In order for the system to be available, at least (n – m ? 1) subsystems must be available Therefore,

A moutofn ẳ X n inmþ1 n! ðn iị! i! A i ð 1 A ị ni

1 ẳ ẵ A ỵ ð1 Aị n ẳ X n iẳ0 n! ðn iị! i! A i ð 1 A ị ni availability can be rewritten as follows:

A moutofn ẳ 1 X nm iẳ0 n! ðn iị! i! A i ð 1 A ị ni 1 n! m! ðn mị! ð 1 A ị m

And the unavailability will be given by (again, for MDT MTBF):

Fig 9.3 Parallel connection of n identical subsystems

UA moutofn ẳ n! m! ðn mị! UA m

MDT is obtained for the case ‘‘m-out-of-n,’’ by the application of previous sections for UA m-out-of-n and MTBF m-out-of-n Therefore,

9.1.4 Summary of Formulas and Results

After establishing the connections between RAMS variables and the components of industrial assets, the next step involves conducting a quantitative assessment of these parameters This assessment allows for the identification of critical subunits or components essential for the optimal functioning of the entire system.

The results obtained can help establish a reliability ranking for components, serving as a preliminary list of recommended spares for warranty assistance, while noting that the initial data are approximations rather than precise values This analysis aims to provide a foundational understanding of the potential behavior of the industrial asset's elements As the design process advances and the company gains experience and detailed knowledge of the systems, these initial values can be refined for greater accuracy, leading to more successful conclusions Following the assessment of product reliability during the design stage, the next step involves analyzing the product once it is in the user's hands, utilizing historical data to verify initial assertions and enabling more informed decisions for future product batches.

Influence of Warranty on the Life Cycle Cost of a Product

In recent years, engineering and operations management specialists have enhanced cost quantification processes by integrating techniques that assess reliability and the impact of failures on the total costs of industrial assets throughout their life cycles These advancements have reduced uncertainty in critical decision-making areas, including design, development, after-sales, maintenance, replacement, and asset acquisition Effective decisions made during the design and manufacturing phases significantly influence the support and maintenance needs of products in the market Key factors affecting reliability—such as quality design, technology, technical complexity, frequency of failures, and maintenance strategies—play a crucial role in determining the total life cycle costs of assets and can extend the useful life of products at reasonable expenses.

9.2.1 Background to Techniques of Life Cycle Costs Analysis

This section examines life cycle cost analysis (LCCA), a key component of the evaluation and control stage in our proposed reference framework It is important to note that various methodologies are available for implementing LCCA effectively.

Table 9.1 Summary chart of formulas

Two subsystems in series Two subsystems in parallel System failure rate k series = k 1 ? k 2 k parallel ẳ k 1 k 2 ð MDT 1 ỵ MDT 2 ị System MTBF MTBF series ẳ MTBF 1 MTBF 2

UA series ẳ UA 1 ỵ UA 2 UA 1 UA 2 UA parallel ẳ UA 1 UA 2

MDT series ẳ MTBF 1 MDT 2 ỵ MTBF 2 MDT 1

3a67e368 0a4d3d50 cf8d5 f476 8201 e328 cbbba50 c741 ebd4f6 b2e1 0316e d218 e1d2 918 up in the LCCA field, and that relate, for instance, to the environmental impact or to the total costs of production assets, etc [11].

While each methodology has unique traits, they generally focus on reliability analysis using a constant failure rate Historical data on Life Cycle Cost Analysis (LCCA) can be found in [12] Notably, significant contributions over the past two decades are outlined in chronological order.

• 1991 (Woodhouse) Presents the LCCA as a systematic process of technical– economical evaluation, taking into account economical and reliability aspects

[13] Presenta el LCCA como un proceso sistemático de evaluación técnico- económica, teniendo en cuenta los aspectos económicos y la fiabilidad [13].

• 1993 (Fabrycky y Blanchard) LCCA model that includes a structured process to estimate Reliability costs [14].

• 1996 (Kirt y Dellisolla) Present the LCCA as an economical estimation technique bound to evaluate in a quantitative form all costs associated to the expected economical useful life span [12].

• 1997 (Woodward) Research line that includes all basic aspects of reliability analysis and its impacts on life cycle costs [10].

• 2000 (Willians y Scott) Model based on the distribution of Weibull to estimate frequency of failure and its reliability costs impacts [15].

• 2001 (Riddell y Jennings) Commercial software development on LCCA and denominated APT Life span [16].

In 2002, Durairaj and Ong emphasized that the swift application of cost analysis techniques allows for the early evaluation of potential design issues, enabling the quantification of their financial impact over the lifespan of industrial assets.

In 2003, the Woodhouse Partnership, in collaboration with the Venezuelan Technological Institute of Petrol (INTEVEP), tested an evaluation model to assess the total life cycle costs of 56 gas compression systems.

The life span cost of a physical asset is determined by identifying its functions at each life phase, estimating the associated costs, and applying these costs during its lifespan extension This valuation encompasses all costs related to design, manufacturing, and production For products launched in the market, some costs must be borne by the buyer Regardless of whether the manufacturer or user incurs these expenses, all costs associated with the product's life cycle are considered From a financial perspective, costs generated throughout the asset's lifespan can be classified into two main types.

9.2 Influence of Warranty on the Life Cycle Cost of a Product 183

• CAPEX: Capital expenses (design, development, acquisition, installation, personnel training, manuals, documentation, tools, and facilities for repairs, spare parts, product withdrawal, etc.).

• OPEX: Operational expenses (labor, operations, planned maintenance, stock, hiring, corrective maintenance, penalization for failures, or low reliability events).

After-sales services are typically provided while production lines are still active, allowing for improvements in product engineering and manufacturing through data from warranty programs, which can lower overall product life cycle expenses By conducting reliability and availability evaluations early in the product development process, companies can identify potential incompatibilities with initial technical specifications for certain configurations If a product is already on the market, this analysis aids in implementing necessary corrections and enhancements, while also anticipating user claims related to unreliability A comprehensive life cycle cost analysis encompasses expenses related to planning, research and development, production, commissioning, warranty, operation and maintenance, and disposal From the consumer perspective, the total cost of ownership includes acquisition costs, operation and maintenance expenses, and disposal costs, factoring in residual value.

Lower budgets for product engineering increase the risk associated with warranty programs, necessitating prompt and thorough analysis of warranty claims for significant failures This analysis is crucial not only for determining repair tasks but also for implementing preventive measures to reduce future claims Conducting a comprehensive review of warranty complaints can reveal patterns and trends related to vendor-buyer issues, quality concerns, manufacturing conditions, and product design flaws.

Fig 9.4 Costs generated throughout the life span of the product

9.2.3 Development of the Stochastic Model

To effectively evaluate warranty services and determine the appropriate warranty period, it is essential to implement strategic measures during the warranty program's planning phase These measures should facilitate the comparison of reliability data and incorporate the cost associated with the product's lifespan Regular reviews of product performance and warranty assistance will enable continuous evaluation and enhancement of the warranty program Companies must establish a standardized method for data collection and analysis, focusing on business-related factors rather than solely industrial metrics The findings should support improvements to the warranty service Various stochastic models can be employed to analyze failure frequencies in systems and repairable units, including the non-homogeneous Poisson process (NHPP) and the generalized renewal process (GRP) The NHPP, often used for simpler repair scenarios, assumes that after a repair, the unit returns to an "as bad as old" (ABAO) condition, making it suitable for minor repair warranty cases Unlike the homogeneous Poisson process (HPP), the NHPP features a failure rate that varies over time, with non-independent and non-identically distributed times between failures.

The rate of occurrence of failure (ROCOF), denoted as k(t), is defined as the inverse of the average waiting time between failures, represented as 1/E[x i] This concept is integral to the Non-Homogeneous Poisson Process (NHPP), which is a stochastic process where the ROCOFs within any interval [t1, t2] follow a Poisson distribution, characterized by its mean k.

9.2 Influence of Warranty on the Life Cycle Cost of a Product 185

0d4204 90efb3ab05fb73 c76 f04 f402 4609 30bbbd8c70 8725 e74dc8 cf9a 5b23 c6 ce52 6d where k(t) is the ROCOFs Therefore, according to the Poisson process,

R t 2 t 1 kðtịdt h i n exp R t 2 t 1 kðtịdt h i n! ð9:5ị where n = 0, 1, 2,… corresponds to the expected total number of failures at time intervals [t 1 , t 2 ] The expected total number of failures is obtained from the function of accumulated intensity:

One of the most common forms of ROCOF used in reliability analysis of repairable systems is the Potence Model Law [24, 25]: kðtị ẳ b a t a b1 ð9:7ị

The article discusses the assumption that the time intervals between successive failures adhere to a Weibull conditional density function characterized by parameters a and b The Weibull distribution is favored in maintenance contexts for its versatility and suitability for various failure processes, although alternatives such as gamma and logarithmic distributions are also viable options.

This model involves that failure ith is conditioned by the operative time until the failure (i - 1)th.

Figure 9.5 illustrates the referenced condition, which arises from the system maintaining the "as bad as old" state following the (i - 1)th repair Consequently, the repair process fails to enhance the lifespan of the component or system To advance this methodology, the notation will be defined as shown in Figure 9.6.

– i: failure event and ‘‘as bad as old’’ repair (from 1 to n) – n: last known failure event

– s: next event after the last known failure (n)

– t i : duration of time, interval between failures – T i : accumulated duration of intervals

According to the mentioned notation in order to get maximum probability estimators (ML) in the parameters of the potency law, the following conditional probability definition is considered:

RðTnị ð9:8ị where F() and R() are the failure probability of components and the reliability on the respective times, respectively Assuming a Weibull distribution from Eq (9.8) can be obtained:

" b # ð9:9ị where in case that the failure event is i = s, then i - 1 = n Therefore, the Weibull conditional function of density is as follows:

For the case of NHPP, there can be obtained different function of probability.

The estimation of time T, which occurs after the last failure and before the next, is crucial for analyzing repairable components Detailed expressions related to this estimation can be found in reference [27] For completed repairable components, the maximum probability function L can be defined accordingly.

Fig 9.5 Conditional probability of failure occurrence t 1 t 2 t 3 ,,, t i ,,, t n-1 t n t s

Fig 9.6 Timeline of failure events9.2 Influence of Warranty on the Life Cycle Cost of a Product 187

Once again, the parameters estimators ML are calculated according to [24, 25].

The results are the following:

The expected total number of failures within the time interval [T_n, T_s] can be calculated by multiplying the interval duration, t_S, by the Weibull accumulated intensity function Here, T_i represents the moment of the ith failure, T_n indicates the total time until the last failure, and n denotes the total number of failures observed.

K ð T n ; T s ị ẳ 1 a b h ð ị T s b ð ị T n b i ð9:15ị where T is the time after the last produced failure and T n is the total accumulated time:

Time till next failure (TNF) from the NHPP [28], taking into account the Weibull parameters and the total accumulated time, will be given by the next expression:

Assuming a Weibull distribution of NHPP, the reliability function will be according to the next expression [28]:

Therefore, the failure probability of the system will be as follows:

9.2.4 Proposed NHPP Model for Warranty Assessment

To estimate the minimum time for the warranty period (t MTW) using the Non-Homogeneous Poisson Process (NHPP), it is essential to gather data on the time intervals (t i, where i = 1,…, n) during which failure events and repairs occurred With this data in hand, the subsequent steps can be carried out effectively.

Taking into account T n as the total accumulated time:

Parameters a and b of the Weibull distribution in the case of the nth event will be then as follows:

Case Study on a RAMS Analysis

The case study here presented corresponds to a practical application referred in this chapter, where a formulation has been developed to apply a RAMS analysis.

The industrial asset under analysis is a device comprising both electrical and mechanical components, which will be externally controlled and powered Based on the examples in Appendix A of ISO/DIS 14224 [32], we can define the device's battery limits, illustrated in Fig 9.8, as a level 0.

Defining the system boundary is essential for understanding the subunits and maintainable items within those limits This process involves careful consideration of various factors to establish clear boundaries for analysis.

(a) It is included only elements of the same class (in this case level 1), which are considered comparable.

(b) It is excluded those items specifically connected across boundaries The failures occurred in a connection will not be attributed to the element connected inside the boundary.

(c) The monitoring and control instrumentation should not be included in this analysis (outside usually).

The previously developed RAMS expressions can be readily applied using a series formulation In this context, if k1 represents the failure rate of the electric system and k2 denotes the failure rate of the mechanical system, the overall failure rate for the complete system can be calculated accordingly.

• k Complete Syst = k 1 ? k 2 The rest variables will be then:

• MTBF Complete Syst: ẳ MTBF 1 MTBF 2

• UA Complete Syst = UA 1 ? UA 2 - UA 1 UA 2

• MDT Complete Syst: ẳ MTBF 1 MDT 2 ỵ MTBF 2 MDT 1

At the second level of analysis, we determine that the industrial asset lacks redundant equipment, allowing us to represent the entire operation using only AND Boolean gates This Boolean representation provides an intuitive understanding of the industrial asset as a cohesive entity The focus of this case is not on evaluating a specific device but rather on demonstrating the practical application of calculations to highlight the advantages of RAMS analysis For a clear depiction of the equipment's functional configuration, refer to the block diagram illustrated in Fig 9.9.

9.3 Case Study on a RAMS Analysis 193

Based on Fig 9.9, let us consider the notation (Table 9.2) for the failure rates, in order to subsequently obtain the corresponding variables subunits level RAMS.

9.3.2 Application of RAMS Variables to the Practical Case

We will further develop the previously discussed RAMS expressions for both the electrical and mechanical systems, allowing for their subsequent application in an in-series formulation For the electrical system, as illustrated in Fig 9.10, the development of these expressions is carried out using the established notation.

• MTBF 1 = [MTBF 11 MTBF 12 /(MTBF 11 ? MTBF 12 )] [MTBF 13 MTBF 14 / (MTBF 13 ? MTBF 14 )]/[[MTBF 11 MTBF 12 /

(MTBF 11 ? MTBF 12 )] ? [MTBF 13 MTBF 14 /(MTBF 13 ? MTBF 14 )]]

• UA 1 = (UA 11 ? UA 12 - UA 11 UA 12 ) ? (UA 13 ? UA 14 -

UA 13 UA 14 ) - (UA 11 ? UA 12 - UA 11 UA 12 ) (UA 13 ? UA 14 -

• MDT 1 = [[MTBF 11 MTBF 12 / (MTBF 11 ? MTBF 12 )] [(MTBF 13 MDT 14 ? MTBF 13 MDT 14 )/

(MTBF 13 ? MTB 14 )] ? [MTBF 13 MTBF 14 / (MTBF 13 ? MTBF 14 )] [(MTBF 11 MDT 12 ? MTBF 12 MDT 11 )/

(MTBF 11 ? MTB 12 )]]/[[MTBF 11 MTBF 12 / (MTBF 11 ? MTBF 12 )] ? [MTBF 13 MTBF 14 /(MTBF 13 ? MTBF 14 )]]

In the same way, the expressions development for the mechanical system (Fig 9.11), yields as follows:

• MTBF 1 = MTBF 21 [MTBF 22 [(MTBF 23 MTBF 24 )/(MDT 23 ? MDT 24 )]/

[MDT 22 ? [(MDT 23 MDT 24 )/(MDT 23 ? MDT 24 )]]]/

[MTBF 21 ? [MTBF 22 [(MTBF 23 MTBF 24 )/(MDT 23 ? MDT 24 )]/

[MDT 22 ? [(MDT 23 MDT 24 )/(MDT 23 ? MDT 24 )]]]]

External Power Complete system boundaries

Fig 9.8 Boundary definition of the industrial asset under study

• UA 1 = UA 21 ? (1 - UA 21 ) UA 22 UA 23 UA 24

• MDT 1 = [MTBF 21 [MDT 22 [MDT 23 MDT 24 /(MDT 23 ? MDT 24 )]]/

[MDT 22 ? [MDT 23 MDT 24 / (MDT 23 ? MDT 24 )]] ? MDT 21 [MTBF 22 [MTBF 23 MTBF 24 / (MDT 23 ? MDT 24 )]/[MDT 22 ? [MTBF 23 MTBF 24 /(MDT 23 ? MDT 24 )]]/

[MTBF 21 ? [MTBF 22 [MTBF 23 MTBF 24 /(MDT 23 ? MDT 24 )]/

[MDT 22 ? [MTBF 23 MTBF 24 /(MDT 23 ? MDT 24 )]]

Fig 9.9 Functional blocks according to subunits

Table 9.2 Notation for failure rates

• General power supply: k 11 • Rotor drive: k 21

• Single-phase power supply: k 12 • Rotor assembly: k 22

• PLC input/output: k 14 • Welding machine: k 24

Fig 9.10 Electrical system block diagram

Fig 9.11 Mechanical system block diagram

As mentioned above, the subunits shown here are constituted by components.

The collected components will yield numerical data on time failure rates and time between failures Utilizing this data along with established expressions, we can accurately estimate the reliability and availability of individual subunits, units, and ultimately the entire equipment.

To facilitate the data handling and the formulation shown here, the treatment is going to be under two possibilities:

• either as if they were identical (taking the value of the most critical one) and arranged in a parallel configuration (hereinafter, case -A-),

• or as if they were arranged in a series configuration (hereinafter, be case -B-).

Maintainable items for electrical and mechanical systems are indicated in Table 9.3.

Taking into account the above-mentioned considerations, the RAMS variables for the electrical system results as given in Table 9.4:

In case -A-, the subindex cxx denotes a critical level 3 component essential for the proper functioning of its corresponding subunit For case -B-, the estimated value (*) assumes an 8-hour repair time for any subsystem Identical subunits apply to sections 1.3 (sensors and clamps) and 1.4 (PLC input-output), where each is a single maintainable item, leading to coinciding variables Additionally, considering these factors, the RAMS variables for the mechanical system are detailed in Table 9.5.

The subindex cxx in case -A- denotes a critical component at level 3, essential for the proper functioning of the corresponding subunit in the electrical system In case -B-, an estimated 8-hour repair time for any subsystem is assumed, denoted by the value (*) By applying the expressions for maintainable items at level 2 to the electric and mechanical systems, the complete robot welder system at level 0 can be analyzed, although this substitution results in complex relations that are challenging to manipulate.

In any case, below it is applied particular numerical data using spreadsheets to obtain useful results.

9.3.3 Application of Numerical Data and Results

After correlating RAMS variables with asset functions, we aim to achieve a quantitative assessment to identify critical components within the system This assessment will highlight which subunits require more frequent preventive maintenance To ensure the effectiveness of these results, it's essential to gather data on component parameters; if that’s not feasible, we can utilize existing databases Currently, several databases, such as the extensive EPRD-97, offer valuable information for this purpose.

Table 9.3 Taxonomy of electrical and mechanical systems

Maintainable item Part or component Maintainable item

General power supply Cable section 6 mm 2 Estator Estator structure

Cable section 16 mm 2 Tube tighter assembly Cable section 10 mm 2 monophase

Protections 5SY6 215-8 Rotor assembly Fixed rotor

Protections 5SY6 308-8 Edge preparation device

Contactor CN20 220 Grip hose cover

Contactor AL12-30-10-24 Rotor driver Auger

Cable section 6 mm 2 Conical tighter

Protections 5SY6 502-7 Interphase worm gear Protections 5SY6 214-7 Welding machine

PLC input/output PLC Others

Table 9.4 Formulation of cases A and B for the electrical system

• MDT 11 = MDT c11 • MDT 11 = (*) Single-phase power supply

The Reliability Information Analysis Center (RIAC), recognized as a Center of Excellence by the U.S Department of Defense, has developed critical databases for parts reliability, including NPRD-95 for non-electronic components Additionally, the Offshore Reliability Data (OREDA) database facilitates the collection and exchange of reliability and maintenance data among international oil companies, enhancing management practices in the oil and gas sector For our case study, we utilized the Failure Rate Data in Perspective (FARADIP) database, one of the largest resources for failure rates and modes, offering comprehensive data across various domains such as electrical, electronic, mechanical, and instrumentation components.

• k ijk = Failure rate = No failures per million hours, and

• MTBF ijk = Mean Time Between Failures = 1/k ijk (910 6 h)

The FARADIP database offers valuable data for assessing each component, specifically addressing two scenarios: case A, which focuses on the critical element for each subunit, and case B, which provides a similar analysis.

Table 9.5 Formulation of cases A and B for the mechanical system

• MDT 21 = MDT c21 • MDT 21 = (*) Rotor assembly

• MDT 23 = MDT c23 • MDT 23 = (**) Welding machine

The analysis presented in Table 9.6 confirms the series configuration of the components under consideration Additionally, please verify the application of the decimal system in Tables 9.6–9.14 and Figures 9.12–9.17, making any necessary amendments.

The analysis of the results enables the extraction of RAMS parameters for higher-level units by utilizing the formulations derived from the block diagrams Focusing on the values from case B, which reflects a more realistic scenario, we can draw meaningful conclusions.

• A ijk = Availability = MTBF ijk /(MTBF ijk ? MDT ijk ) 9 100

(*) It has been assumed in the table an estimated time of 8 h for the repair of any subsystem [7] With the above consideration, we obtain the values shown in Table 9.7.

Here, the parameters have been obtained for the whole system RAMS by applying an in-series formulation.

Based on the above information, it is going to obtain the reliability values R(t).

For that purpose, it is going to get R(t) assuming a mixed behavior of the elements

[35] (Table 9.8) That means, the mechanical components will follow a Weibull distribution with b = 0.5 (cells with white background) and electrical components will follow an exponential distribution b = 1 (cells with gray background).

Representing these values graphically, it is possible to observe the evolution for items maintainable over a year (Fig 9.12).

In the same way, the graphical evolution of mechanical and electrical systems, as well as the complete system, will be (Fig 9.13).

After one year of reliability assessment, we established a priority and criticality matrix that ranks maintainable items from lower to higher reliability This preliminary list of recommended spares is derived by identifying items with an 80% decline in reliability post-operation Additionally, within this subset, we select components whose failure rates represent 80% of the total failure rate for each maintainable item, adhering to the Pareto principle.

Case Study on the Life Cycle Cost Analysis

Different types of warranties are suitable for various products, and in this case, we focus on a commercial product where the warranty is negotiated directly with the customer Additionally, there are options for extending the warranty and exploring other after-sales contracts.

The customer is interested in acquiring, using, and maintaining a specific engine developed and tested by the manufacturer, with some already in operation Given the extensive performance data available, the service company can offer a warranty period after maintenance services, ensuring the repaired engine achieves 80% availability This availability period will be determined based on the organization's risk tolerance and will utilize two stochastic methods: NHPP for simple repairs and GRP for complex repairs Since this scenario involves a complex repair, the GRP method will provide the most suitable results for establishing the warranty period.

The manufacturing company possesses historical data on engine behavior, which is illustrated in Table 9.10, showcasing failure and repair events over time The defined time intervals, t i (where i = 1,…, 6), provide a structured framework for analyzing these occurrences.

By utilizing the established formulas and specified values, we can derive key metrics such as a n, b n, TNF n, t MTWn, K, R(T s), and F(T s) To assess the influence of the Non-Homogeneous Poisson Process (NHPP) on the calculation outcomes, we will evaluate the system's behavior with varying known event counts, specifically analyzing scenarios where n equals 4, 6, and 8.

Applying the process for n = 6 and n = 4, we obtain the results shown in Tables 9.11 and 9.12.

Table 9.6 Results for cases A and B ij Maintainable item (Level 8 ISO14224) -A- -B- l ij = n 9 k ijk l ij = Rk (k ijk )

The results presented in Table 9.7 highlight the performance metrics of various maintainable items categorized under Level 8 ISO 14224 The general power supply exhibits a mean time between failures (MTBF) of 47.00 hours and an availability (A) of 99.96% The single-phase supply shows a significantly higher MTBF of 6.500 hours with an impressive availability of 99.99% Clamps sensors have a MTBF of 10.00 hours, maintaining an availability of 99.99% The PLC input/output system has a MTBF of 50.00 hours and an availability of 99.96% In the rotor driver category, the MTBF is 23.00 hours with an availability of 99.98%, while the rotor assembly and stator show MTBFs of 180.506 and 155.000 hours, respectively, with availabilities of 99.86% and 99.88% The welding machine presents a lower MTBF of 315.600 hours but maintains an availability of 99.75% At the subunit level, the electrical system has a MTBF of 113.50 hours and an availability of 99.88%, while the mechanical system shows a MTBF of 23.002 hours with a high availability of 99.99% Finally, the complete industrial asset system achieves a MTBF of 136.502 hours and an availability of 99.88%.

9.4 Case Study on the Life Cycle Cost Analysis 201

Table 9.8 Reliability matrix for a mixed distribution

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec days/month 31 28 31 30 31 30 31 31 30 31 30 31

AFTER-SALES SERVICE OF ENGINEERING INDUSTRIAL ASSETS

A REFERENCE FRAMEWORK FOR THE WARRANTY MANAGEMENT

MAIN POWER SUPPLY SINGLE PHASE POWER SUPPLY CLAMPS SENSORS

PLC INPUT/OUTPUT ROTOR DRIVE ROTOR ASSEMBLY

Fig 9.12 Reliability evolution along a year for maintainable items

ELECTRICAL SYSTEM MECHANICAL SYSTEM COMPLETE DEVICE

Fig 9.13 Reliability evolution along a year for systems

Table 9.9 Priority order and criticality matrix ij Element R (8.760 h)

C Estator Rotor assembly Welding machine

B General power supply Rotor driver

A Single-phase supply Clamps sensors PLC input/output

Applying different percentages (80, 60, and 40 %) for reliability, we can obtain different times as recommended warranty period based on the time till next failure.

Choosing between different MTWn options becomes easier when we understand the anticipated failure rate (K) and the system reliability (R(Ts)) In this analysis, a one-year operational period post-repair (Ts = 8,760 hours) has been taken into account for the calculations.

This exercise highlights the impact of reduced failure and repair events on system reliability and the time until the next failure A detailed analysis of these cases over time reveals significant differences in system reliability The calculated parameters are influenced not only by the number of failures but also by their sequence Even a few divergent failures can skew the results, as demonstrated in the first four events (e.g., event 3, t i = 3.12800 h) Therefore, it is essential to focus on convergent failure times to prevent the mixing of different failure modes.

Different warranty risk assumptions lead to varying outcomes in the minimum warranty period values, as illustrated in Table 9.13 The evolution of R(T s) over two years following events n = 4 to 8 is depicted in Figures 9.14 and 9.15, for T s values of [2,190, 4,380, 6,570, 8,760, 10,950, 13,140, 15,330, 17,520].

This exercise contributes to illustrate the calculation of warranty periods.

Exploring the impact of warranty policies on the time until next failure (TNF) can provide valuable insights By considering TNF as a variable, companies can assess the effect of different warranty policies on their risk levels For instance, setting a maximum probability of failure during the warranty period, such as 20%, 30%, or 40%, can result in varying warranty periods Notably, the higher the probability of failure, the steeper the warranty curve, indicating a more significant decrease in warranty time as the risk of failure and repair increases.

Table 9.10 NHPP engine historical data related to time per warranty event (n = 8)

In addition to the previously discussed exercise illustrating warranty period calculations, we can now explore the GRP model to determine various warranty parameters For our second example, we will analyze the same repair events and present the results in Table 9.14.

In addition, now for the GRP model, Figs 9.16 and 9.17 show the evolution of R(T s ) along 2 years after the events n = 4, …, 8 have taken place for T s = [2,190, 4,380, 6,570, 8,760, 10,950, 13,140, 15,330, 17,520].

In the GRP model, a higher failure probability correlates with a steeper warranty period curve, indicating that companies taking on greater risks in their warranty policies will experience a more pronounced increase in warranty durations The reliability adjustments derived from the GRP model in relation to time and the anticipated number of failures demonstrate its superior fit for analyzing warranty effectiveness.

Table 9.13 NHPP results obtained with n = 8, n = 6, and n = 4 n = 8 n = 6 n = 4 an 18,107.47 18,594.02 19,471.96 bn 1.562172 1.685553 2.253470

The inclusion of the parameter q is detailed in Table 9.15, which compares the NHPP and GRP models based on their likelihood values, highlighting their respective adjustments.

GRP is a general model, providing a way to describe the rate of occurrence of events over time understanding the effects of the repairs on the age of that system,

Fig 9.14 NHPP reliability evolution depending on time and the amount of events

Fig 9.15 NHPP surface representation of R(t, n)

The renewal process in the context of NHPP representation involves systems that undergo repairs after failures, resulting in a state that is neither completely restored to new nor left in its previous degraded condition Instead, these systems experience partial rejuvenation post-repair, highlighting the importance of understanding their performance and reliability in this intermediate state.

The warranty period determined in Exercise 1 represents a minimum value derived from a Non-Homogeneous Poisson Process (NHPP) model, factoring in various percentages of waiting TNF (20%, 40%, and 60%) The company must now evaluate the appropriateness of this warranty period and consider the implications of extending it, which would lead to increased warranty costs Consequently, calculating this percentage is a critical step in the decision-making process.

Understanding the risks associated with the warranty period is crucial for companies, as it allows for better planning and resource allocation By utilizing the NHPP model, manufacturers and subcontractors can accurately predict the timing of the next warranty service, especially when the warranty duration is predetermined in repair orders or maintenance contracts This proactive approach helps in budgeting for warranty services and ensures a technical team is prepared for any future issues The NHPP model has proven effective in real-world scenarios, demonstrating a conservative approach and manageable mathematical expressions, making it an ideal choice for this analysis.

Application of ICTs in the Process of Warranty

10.1.1 The E-technology Concept in the Warranty

The success of a warranty program heavily relies on maintaining a strong customer relationship and continuously improving warranty management through the adoption of emerging technologies The introduction of "e-warranty," a component of "e-manufacturing" and "e-maintenance," leverages advanced information and communication technologies to enhance warranty management in a collaborative, multi-user environment E-warranty encompasses essential resources and services that facilitate proactive decision-making, alongside traditional warranty activities such as monitoring, diagnostics, and prognosis To achieve higher product quality and effective technical assistance, the involvement of after-sales technicians is crucial, necessitating increased knowledge, experience, and training While some processes will evolve into "e-processes" through these technological advancements, others will remain unaffected, marking a significant shift in warranty program management.

Manufacturers can leverage the Internet to gather real-time data from equipment under warranty, thanks to pre-installed sensors that monitor key metrics like temperature, runtime, and pressure This continuous diagnostic capability enables predictive maintenance by identifying potential failures due to equipment malfunctions or improper usage The e-warranty model enhances traditional warranty management by integrating web services and collaborative monitoring, serving as a strategic marketing tool that allows users to extend their warranty contracts through remote product performance tracking Ultimately, this innovative customer service model bridges the gap between manufacturers and customers, transforming companies into manufacturing service providers that offer support anytime and anywhere through advanced ICT solutions.

10.1.2 Technologies Applied to the Technical Assistance

The application of ICT in maintenance, particularly in warranty management, introduces innovative processes that enhance the performance of technical assistance.

1 Remote assistance Using tools for remote access to information (Internet, Bluetooth, etc.), the warranty service technicians are able to access the product which presents a failure or where a complaint has been made, allowing them the remotely start-up, control, configuration, condition monitoring, data collection, and analysis of the product One of the biggest advantages is to connect products distributed in different and distant geographic locations, to a warranty service center that allows a remote decision-making.

2 Cooperative warranty service The e-warranty would allow implementing an information infrastructure connecting clients (users) with suppliers (manufacturers) or connecting engineers and technicians with the products using Internet.

The resulting platform would allow then a strong cooperation between different areas of the company:

• Production (to implement changes in the manufacturing process).

• Purchasing (acquisition of a specific spare part).

• Engineering (change in the product design).

• Quality (to certify the compliance of the product itself and/or the repair works performed on it).

• Logistics (to control spare parts inventory and to calculate the minimum path to transport those spares to the place where the related device is located).

• After-sales or management team (to assign teams, tools, materials, planning, etc., when the failure cannot be repaired remotely).

By minimizing process errors and optimizing communication, we enhance bidirectional flow, generate valuable feedback, and ultimately improve both the quality of service and client perception.

3 Online assistance The remote follow-up of sold units during the warranty period, together with the possibility of programming status alerts, allows the manufacturer or supplier to respond quickly to any situation and even before the user has been detected failure, preparing accordingly any intervention in an optimal way.

4 Predictive warranty service The e-warranty would allow a failure prediction in those units offered for sale, taking into account the product current state and the intended use on it, together with the life predictions on component performed by the different manufacturers, and obtained through a reliability analysis (RAMS analysis) [1].

5 Failure diagnosis The e-warranty allows technicians to carry out online diagnosis to those occurred failures, as well as to suggest solutions to the end user.

Consequently, it reduces the communication time between supplier and customer, improving the quality of the shared information and, therefore, the resolution time.

10.1.3 Influence on the Proposed Management Framework

The proposed warranty assistance management framework incorporates various tools and methodologies designed to effectively handle extensive warranty-related data Central to this framework is the "e-warranty" stage, which is part of a dedicated block focused on enhancing the overall warranty program.

The enhancement of management performance, aligned with the company's adopted policy, necessitates a computerized information system for the warranty program This system enables cyclical data management and result analysis, incorporating the e-warranty concept E-warranty streamlines decision-making by processing large volumes of diverse data from multiple sources It represents the application of information technology in after-sales service management, particularly in data storage and analysis related to consumer complaints This multidisciplinary approach to warranty management underscores the importance of ICTs in optimizing operational efficiency.

The approach, akin to Six Sigma methodology, focuses on monitoring, diagnosing, predicting, and controlling products in real-time while detecting abnormalities Diagnosis reveals potential causes of early degradation or failure, which is crucial for root cause analysis, while prediction assesses the failure's impact on the product for criticality analysis This enables manufacturers to determine if a failure under warranty is covered or due to misuse With real-time data, manufacturers can proactively alert users to anomalies, recommending preventive measures like equipment shutdown to minimize repair time and costs, benefiting both parties Additionally, the gathered information facilitates decision-making and maintenance actions, automating work orders and expediting administrative processes Historical data may suffice to identify failure causes, negating the need for physical assessments before repair planning.

1 Analysis of customers and complaints.

3 Prioritization in the decision-making.

4 Analysis of the failure impact on the product.

5 Identification of possible degradation causes or anticipated failure.

6 Modernization of technical assistance plans.

7 Processing of large volumes of information.

8 Update of reliability data and failure rates.

9 Data feedback on the product life cycle cost.

Emerging processes in warranty management, driven by innovative information and communication technologies (ICT), include risk-cost-profit analysis, life cycle cost, and RAMS analysis While customer communications typically utilize ICTs such as email and mobile phones, they do not qualify as emergent processes By adopting a cyclical approach to continuous improvement in warranty management, the integration of new technologies enhances customer service and creates a feedback loop within the management framework, utilizing real-time information and digital data from market-launched units.

The e-warranty system leverages remote sensor signals to monitor product performance, enabling predictive maintenance during the warranty period This innovation significantly reduces administrative tasks, enhances operational uptime, and optimizes equipment efficiency Customers may also have the option to extend their e-warranty, utilizing the pre-installed sensor network to foresee potential failures that could disrupt equipment functionality or impact production lines Additionally, the e-warranty platform alerts manufacturers online about any issues, ensuring timely interventions.

• There is a failure in equipment.

• Before the failure occurs (alarms), and

• When the equipment reaches certain conditions in its operation.

The system enables real-time access to essential information for both customers and manufacturers through any Internet browser, allowing manufacturers to receive detailed alarm notifications promptly.

Warranty Risk- Cost-Profit Analysis

Información and Communication Technologies in Warranty

Fig 10.1 ICTs influence on the proposed warranty framework10.1 Application of ICTs in the Process of Warranty Management 217

When a failure occurs, the system promptly gathers information and, if feasible, dispatches the necessary technical and material resources to address the issue, while also informing the customer about warranty or maintenance requirements Predicting equipment failures benefits both customers and manufacturers during the warranty period, as it helps customers minimize equipment downtime and reduces potential damage This proactive approach leads to shorter repair times and significantly lowers labor and material costs for manufacturers Ultimately, this results in fast, effective service that enhances equipment productivity and customer satisfaction It is essential that the application of these services is clearly outlined in the acquisition contract for industrial assets to prevent any conflicts regarding customer privacy.

The e-warranty system is an advanced proactive solution that automatically and instantly gathers essential data from equipment, allowing users to customize the type of information received based on specific analysis needs, such as failures, performance metrics, and anomalies in measurable parameters like temperature and pressure This system not only enhances operational insights by monitoring workload peaks and equipment status but also offers additional advantages that improve overall equipment management and efficiency.

• It eliminates spatial barriers between customer and manufacturer.

• It eliminates the time barriers.

• It reduces the cost per failure to the customer and manufacturer.

• It collaborates in the organizational familiarity with ICT.

• It enables permanent access and control in real time to all that information on the equipment under warranty.

• It facilitates fast communication between customer and manufacturer.

• It eliminates paperwork for the manufacturer in case of equipment failure (cause verification, repair record, etc.).

Management of Customer Relations in After-sales Service

In today's competitive landscape, businesses increasingly prioritize warranty management processes, particularly when faced with high-stakes responsibilities and costs that could impact market demand and customer retention This oversight can lead to missed opportunities for substantial cost savings and hinder the potential for enhancing overall business value.

To achieve better-quality products and enhance customer satisfaction, it is essential to consider the interactions between engineering, marketing, and after-sales support at both operational and strategic levels Consequently, warranty management should be viewed not merely as a cost center but as a proactive element that can add significant value to business performance.

• Improving the reclamation response time (speeding up their process).

• Decreasing reclamation costs (giving them an automatized treatment).

• Reducing personnel in charge of the reclamation process.

• Reducing the loss of customers due to the poor quality of the product.

• Improving distribution costs (speeding up the information flow with suppliers).

Improving after-sales service through efficient tools, integrated systems, and a well-structured organization can significantly reduce warranty costs, enhance product quality, and boost customer retention The integration of new technologies fosters greater knowledge, experience, and technical training within service teams A key component of a successful warranty management program is the relationship with customers, which is often managed through customer relationship management (CRM) systems These systems not only define customer-centric business strategies but also include IT applications for organizing and managing customer data and complaints, typically as modules within enterprise resource planning (ERP) software While CRM initially focused on marketing and sales, its adaptation for warranty management enables companies to optimize their customer engagement and service delivery.

• Identify products and services requiring assistance.

• Reduce the time of the assistance and optimize channels of information.

• Identify groups of customers in order to develop common strategies.

• Be conscious of customer’s real needs after the sale.

• Increase sales on the same level as customer satisfaction, etc.

Customer relationship management (CRM), whether integrated within an ERP system or functioning as a standalone solution, encompasses both operational functions that engage directly with customers (front office) and analytical processes that connect with various internal departments (back office).

A robust CRM strategy relies on a comprehensive database that offers insights into claims, recurring failures, and concealed defects, along with quantitative and qualitative analyses and statistical outcomes.

10.2 Management of Customer Relations in After-sales Service 219

Effective warranty program management should be strategically integrated with technical and commercial planning from the onset of product development By providing after-sales support while production is ongoing, valuable insights can be gathered that enhance both the production process and the overall design and development of the product.

When developing an after-sales strategy, it's essential to consider various international standards that influence the entire business activity, in addition to understanding the product life cycle.

The management process outlined in quality management systems and standards typically encompasses key features, enabling the development of a reference framework for warranty management However, some essential information required for this closed-loop process may not be readily available from the outset Consequently, adapting project steps to the framework's phases undergoes an evolution, with the design and development stage serving as the ideal time to formulate a strategic warranty program through an initial balance scorecard and approximate product behavior evaluation This analysis yields valuable insights into the product's performance capabilities, spare part costs, and repair times, ultimately informing the development of an effective warranty program.

The prelaunch stage is an ideal time to explore the integration of new e-technologies, including e-monitoring, e-diagnosis, and e-prognosis through remote devices Following this preliminary phase, the launch stage is significantly shaped by production and marketing efforts From the proposed framework perspective, it is essential to initiate new steps and iterations within our closed loop system.

The RAMS analysis results can guide the development of an initial maintenance plan tailored to the warranty period, aiding in warranty capacity planning, spare parts provisioning, task scheduling, and technician skill assessment Additionally, insights from previous studies on product life cycle costs during the prelaunch phase enable an initial evaluation of Warranty Policy Risk-Cost-Benefit During the launch stage, implementing a Customer Relationship Management (CRM) system is crucial for formulating a client-centered business strategy Finally, in the post-launch stage, all components of the proposed framework will be fully operational, highlighting the importance of criticality in the overall process.

LAUNCH STAGE PRE-LAUNCH STAGE POST-LAUNCH STAGE Step 1: EFFECTIVENESS Balance Score Card

Criticality Analysis Failure Root- Cause Analysis

Maintenance Design Tools adapted to Warranty Cost-Risk-Profit Analysis

6 sigma, TPM ICTs applied to Warranty Customer Relationship Management Step 3: ASSESSMENT AND CONTROL

Life Cycle Cost Analysis Reliability, Availability, Maintenability and Safety Step 1: EFFECTIVENESS Balance Score Card Criticality Analysis Failure Root- Cause Analysis

Life Cycle Cost Analysis Reliability, Availability, Maintenability and Safety Step 1: EFFECTIVENESS Balance Score Card Criticality Analysis

Life Cycle Cost Analysis Reliability, Availability, Maintenability and Safety Fig 10.2 Framework evolution, according to the industrial asset life cycle10.2 Management of Customer Relations in After-sales Service 221

The analysis based on risk-cost evaluates the likelihood of an event occurring alongside its potential impact This article explores the effectiveness of implementing a new management philosophy, such as Six Sigma, which combines human factors with statistical improvement tools Future iterations of the proposed warranty management framework will focus on warranty logistics, aiming to achieve a balance between costs and customer satisfaction.

10.2.2.2 Legal Aspects on the Warranty Management

The strategic management of the product life cycle from a warranty perspective leads to the consideration of warranty extensions, which can be formalized through a contract outlining the conditions for extended assistance While warranty is often referred to as a "service contract," key differences exist; specifically, a service contract is typically purchased separately, whereas a warranty is included with the product purchase Consequently, a warranty extension can be viewed as a type of service contract, potentially mirroring the original warranty's scope or differing in its terms Typically, discussions regarding warranty extensions occur close to the end of the warranty period, and if both the buyer and seller agree, the extension is formalized Legally, warranties and their extensions are defined through a contract that provides specific assurances to customers for a set duration.

W and L are the warranty and the extended warranty period, respectively).

A warranty can be applied to purchased products or services, ensuring a specific workmanlike quality Warranty extensions may outline different technical service conditions provided by the manufacturer, creating a legal obligation between the manufacturer and the buyer Buyers generally have an inherent understanding of warranties, which exists independently of written agreements Sold products and those with extended warranties must meet ordinary user expectations, and sellers must ensure items are suitable for their intended purpose Countries that have ratified the United Nations Convention on Contracts for the International Sale of Goods (CISG) mandate that sellers provide goods fit for ordinary use unless otherwise agreed In contrast, under American law, if a seller knows of a buyer's specific needs and the buyer relies on the seller's expertise to provide appropriate goods, similar obligations apply.

Implied warranties ensure that products are fit for their intended purpose and meet applicable trade standards Under the Uniform Commercial Code (UCC) in the USA, sellers can disclaim these warranties, which must be clearly indicated in the contract Additionally, laws such as the Magnuson-Moss Act address warranties for consumer products used commercially In Europe, consumer protection laws outline seller responsibilities and consumer rights regarding warranties and after-sales services, focusing on repair and replacement guidelines.

Users will incur no charges for repairs, as all necessary expenses to address product non-conformity with the contract—including shipping, handling, labor, and materials—will be covered.

The Methodology Six Sigma in After-sales Warranty

The proposed warranty management reference framework emphasizes the fourth step of continuous improvement, which relies on widely accepted indicators Insights gained from the previous steps in the framework can significantly enhance this process.

POLICY 2 Limitation on individual Costs

2 Remaining items to be borne by the buyer

Claims under warranty are attended

1 If cost < a limit, buyer pays nothing

2 If cost > a limit, buyer pays the excess cost

POLICY 3 Limit on Total Costs

Obligation ceases when comes first:

1 Total repair cost > a specified limit or

2 End of the extended warranty period

POLICY 2 Limitation on individual Costs

1 Rectification of specific components at no cost over the extended warranty period

2 Remaining items to be borne by the buyer

Claims under warranty are attended

1 If cost < a limit, buyer pays nothing

2 If cost > a limit, buyer pays the excess cost

POLICY 3 Limit on Total Costs

Obligation ceases when comes first:

1 Total repair cost > a specified limit or

2 End of the extended warranty period

Fig 10.4 Possibilities for the warranty extensions (adapted from [10])

The increasing complexity of data in after-sales services presents a significant challenge in terms of information management and discrimination between useful and irrelevant data To address this issue, the integration of new technologies is crucial for processing large volumes of data from multiple sources, while management applications can facilitate informed decision-making and contractual customer relationships However, to ensure the effective implementation of these tools, a quality methodology is essential, serving as the backbone of management and organizational processes In this context, the Six Sigma method emerges as a viable solution, offering a structured approach to quality management and continuous improvement, with potential applications in after-sales services, particularly when combined with other management and quality methodologies.

10.3.1 Brief Description of the Method

To enhance the efficiency of warranty service management, it is essential to implement programs and methodologies that foster organizational improvement Concepts from Total Productive Maintenance (TPM) can be adapted to achieve continuous enhancement in maintenance applications This goal aligns with other methodologies, such as Total Quality Management (TQM) and the ISO-9000 family, which serve as foundational reference frameworks Recently, many organizations have begun adopting Six Sigma, a management philosophy that combines the human element with statistical improvement tools, to optimize after-sales service Six Sigma addresses variability, a key negative factor affecting quality, by proposing measures aimed at reducing this dispersion.

Table 10.1 Example guideline for a service contract on warranty extensions

• Extended period • Remedying of warranty defects • Damaged products

• Costs for replacement of components, repair, etc.

• Geographic area • Non-refundable costs • Changes in design

• Warranty defect • Replaced components • Measurements

• Service and maintenance • Products sold by other vendors • Limitation of liability

• Payment • Refund, payment of compensation • Force majeure

• Notice of warranty claim • Normal wear and tear • Representations10.3 The Methodology Six Sigma in After-sales Warranty 225

• To select those indicators or variables that are critical for quality.

• To measure these variables so that real data are gathered from the current situation.

• To detect the variation source of the variables of interest and their admissible tolerances.

• To apply statistic controls that allow the medium- and long-term improvements.

The implementation of the Six Sigma philosophy necessitates the use of extensive data and numerous variables, particularly when integrated with modern electronic information and communication technologies, leading to significant improvements in warranty management and service sectors A dedicated, full-time team is essential for this methodology, particularly in customer technical assistance, where the team should consist of mid-level managers independent from after-sales, engineering, manufacturing, or quality departments, functioning autonomously to resolve customer complaints Ultimately, Six Sigma focuses on three key objectives: enhancing customer satisfaction, reducing assistance cycle time, and minimizing defects For effective implementation, an organized group of individuals is required.

A BLACK BELT is a key figure responsible for managing significant change opportunities and achieving optimal results, serving as an expert in problem-solving utilizing Six Sigma methodologies.

The Master Black Belt serves as a trainer, consultant, and overseer for Black Belts, showcasing expertise in Six Sigma tools This role is crucial for ensuring efficient performance within teams and groups, driving continuous improvement and excellence in processes.

Green Belts are trained in Six Sigma methodologies, distinguishing them from Black Belts primarily by their dual roles within an organization While Black Belts focus exclusively on process improvement, Green Belts typically hold other full-time positions and contribute part-time as team members or leaders.

In the Six Sigma methodology, the CHAMPION role is typically filled by a high-ranking executive who sponsors a GREEN BELT or a team These individuals are crucial managers responsible for driving significant changes within an organization.

• IMPLEMENTATION LEADER The implementation leader is a professional in the field of business improvement.

DMAIC teams play a crucial role in managing quality processes and addressing company issues that impact both customer satisfaction and the organization’s financial performance.

DMAIC, an acronym for "define, measure, analyze, improve, and control," is a structured approach used by teams to enhance processes and solve problems Each team operates under the guidance of a BLACK BELT or GREEN BELT, who supervises specific tasks aimed at achieving measurable results.

The DMAIC process is reviewed by a Master Black Belt, who is a champion and serves as the implementation leader Each component of the DMAIC acronym involves specific actions that contribute to effective project management and process improvement.

• DEFINE There is a need to consider the program framework as a whole Groups must define what the considerations of a problem are and how to visualize it.

• MEASURE It has two main objectives:

– Gathering data to validate and quantify the problem.

– Obtaining key indicators for problem resolution.

• ANALYZE Once the information is gathered, it must be analyzed, and the criteria for problem resolution must be set out.

• IMPROVE This is the stage where problems are identified and solved, adapting the necessary measures to prevent them from occurring again.

• CONTROL This is the part that is in charge of localizing defects and prevents them from occurring again.

10.3.2 Interaction of the Six Sigma with Other Tools and Methodologies

Six Sigma is a mature and versatile methodology in corporate management, designed to achieve and optimize results effectively By utilizing a combination of statistical and management tools, it enables companies to achieve significant short-term improvements Implementing Six Sigma enhances customer satisfaction and increases company value by eliminating non-value-added activities Overall, adopting this methodology reduces costs, boosts productivity, and improves customer benefits, while addressing fundamental questions about process flow, key stakeholders, and objectives.

Fig 10.5 Organization for the implementation of Six Sigma10.3 The Methodology Six Sigma in After-sales Warranty 227

3a67e368 0a4d3d50 cf8d5 f476 8201 e328 cbbba50 c741 ebd4f6 b2e1 0316e d218 e1d2 918 does the customer expect from it? What are parameters used by the managers and the people responsible for controlling it?

Cultural influences significantly impact the implementation of methodologies like Six Sigma, as the context and type of company play crucial roles These factors often lead to specific trends and interactions that combine Six Sigma with other quality tools, highlighting the importance of tailored approaches in diverse organizational environments.

The application of integrated Lean techniques to statistic tools is a solid fact.

And it is gaining popularity The combination properties of this technique allow an easier simulation of processes with the aid of computer information technologies

Lean methodology, as illustrated in Fig 10.7, enables the elimination of non-value-adding activities while fostering a streamlined flow of processes This approach primarily aims to minimize various forms of waste.

VSM – Decision what tool to use Visual management – Focus to abnormalities management

DMAIC FMEA Fishbone Kitting C&E VMI Control Charts

Participation of employees Learning doing Problem solving

Fig 10.6 Methodologies to improve customer satisfaction (adapted from [32])

These Lean tools include continuous processes of analysis (Kaizen), production

‘‘pull’’ (Kanban), and elements and failure-proof processes (Poka-Yoke).

(b) DFSS: Design for Six Sigma

The DMADV system, which stands for define–measure–analyze–design–validate, is gaining traction for enhancing creativity and innovation by incorporating TRIZ tools, a theory of inventive problem-solving Design for Six Sigma (DFSS) emphasizes a rigorous approach to product and service design aimed at exceeding customer expectations Companies utilizing Six Sigma often identify design-related defects, prompting the need for DFSS to redesign manufacturing processes and initial capacities This approach ensures that final products are produced with fewer defects by integrating engineering and design processes, effectively eliminating potential defects before they arise.

Extensions to the Framework

Background

Warranty assistance encompasses various disciplines, including Management, Human Resources, and Environmental Management, requiring a deep understanding of the product to effectively support customers This service becomes critical when product failures occur, prompting user claims that create pressure on the organization Quick decision-making is essential in these scenarios, complicating the process of balancing cost reduction, production impact, urgency, and customer service quality Decisions may not always be universally accepted within the organization, highlighting the importance of acting with diligence and professional ethics to address the potential social implications of the choices made.

Effective customer service management is essential as it directly interacts with customers and addresses their needs In customer-oriented organizations, the customer service department plays a crucial role in enhancing customer satisfaction through high-quality assistance, while also enriching the overall service experience of the organization Furthermore, knowledge management is vital, as it facilitates the extensive exchange of information both internally and externally, supporting operational efficiency.

Updating and sharing knowledge related to technical assistance for maintenance and warranty incidents is essential To enhance this knowledge, activities like coaching, mentoring, and on-the-job training are employed However, these activities can be challenging, as many procedures and technical instructions are based on "laboratory conditions" rather than real-world operating environments Once products are launched and distributed among various users, the impact on physical assets can vary significantly Therefore, investing in human capital is vital for ongoing improvement and effectiveness.

Human Resources, Security and Law

Technical assistance Services and incidents

Warranty Ser vice s a nd incide nts

Training Perf o rmance Res trictions an d warnin

Ma gs teri als n eed s

Plan and im provem ents

Human Resources, Security and Law Business Strategy and

Rel iabili ty Standards and

Fig 11.2 Information flow among after-sales service and other entities

244 11 Intellectual Capital in the Technical Assistance

To enhance customer service and create a competitive advantage, companies must leverage human capital, which encompasses knowledge, skills, attitudes, interests, and competencies Effective management of human resources requires evaluating technical aspects such as staff adaptability, learning capabilities, teamwork, and the ability to handle diverse tasks Assessing the value generated by customer service is complex and requires multiple perspectives This section introduces a methodology to quantify the benefits of after-sales service management for companies with distributed products, focusing not only on the advantages but also on minimizing risks related to reliability.

After-sales Service Contribution in a Company

This article evaluates the impact of various departments on a company's customer service, focusing specifically on the maintenance department By comparing insights from different authors, we can understand how customer service is influenced by this area.

Management is an essential discipline that focuses on effectively leading activities and resources—such as skills, knowledge, and responsibilities—toward achieving specific objectives This process is crucial for enhancing control and facilitating knowledge management within organizations.

Effective customer service plays a crucial role in finance and the economy, as it can lead to substantial savings for companies by minimizing the impact of failures and preventing more serious incidents.

• Business—Functionality Customer service is aimed at maintaining the product functions, once it is already in the hands of the client, in order to fulfill the expected functions satisfactorily.

• Quality and customer relationships Customer service can increase its contribution to gaining customers and customer satisfaction and retention.

After-sales service is crucial for safeguarding both internal and external resources, significantly impacting safety With increasing societal interest in environmental protection, customer service objectives must prioritize the conservation of industrial assets while ensuring safety for the environment and individuals, in line with relevant legal regulations.

Enhancing products and services through technical assistance fosters continuous process improvement, focusing on value creation and the agility to adapt swiftly to changes.

To effectively assess contributions in various areas, it's essential to utilize historical data and consistently apply performance indicators These indicators serve as valuable tools for decision-making and enhancing technical assistance In after-sales services, where customer interaction is significant, evaluating performance should include warranty activities and claims impact analysis It's important to approach customer service contributions in failure analysis probabilistically, acknowledging the inherent uncertainties of failure occurrences This involves studying random variables like Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR), which are defined by their probability distribution functions.

[25] The importance of the claims is not only relevant in terms of operational performance, but also in terms of costs [26] and the life cycle phases of industrial assets (Fig 11.4).

The risk-cost model simplifies decision-making by emphasizing higher benefits through reduced costs and minimized impact Post-sales costs (CP) encompass planned activity expenses, corrective costs related to claims, and additional risk-related costs linked to production, safety, reliability, and product quality, all of which can influence customer service.

CP ẳ C Planned ỵ C Corrective ỵ C Risk production ỵ C Risk safety ỵ C Risk reliability ỵ C Risk quality : ð11:1ị

Summarizing, we could classify after-sales service costs based on their impact into two categories [20, 27, 28]:

COMPANY STRA TE GY AFTER SALES SERVICE

Fig 11.3 Contribution between after-sales service and business strategy

1 Direct costs such as planned and corrective costs.

2 Costs associated with risks in order to quantify the consequences due to the lack of reliability, environmental impact, production, and quality.

Risk costs can be expressed as:

• P r is the probability that a complaint can be issued

• C Consequence is the resulting cost of a specific complaint

• i is the type of possible failures (1, 2,…, n).

To fully understand after-sales service costs, it's essential to evaluate direct expenses and the risks associated with reliability issues These costs significantly influence the customer service organization's ability to generate benefits, such as reduced expenses and increased savings for the company Ultimately, these measurements help gauge the intellectual capital of customer service.

The Technical Assistance as Intellectual Capital

A knowledgeable and experienced technical support team is a strategic asset that provides a competitive advantage in the industry To evaluate this human capital effectively, the American Accounting Association (AAA) has established a set of nonfinancial indicators that aid in decision-making Numerous studies have been conducted on the valuation of costs generated throughout the product life cycle.

11.2 After-sales Service Contribution in a Company 247

The measurement of intellectual capital presents significant challenges, particularly when addressing intangible issues that are difficult to quantify and replicate It is widely recognized that knowledge serves as a competitive advantage for companies, with the potential to yield future benefits Defined by Euroforum in 1998, intellectual capital encompasses all intangible assets within an organization that, while not captured in traditional accounting, contribute to or have the potential to enhance company value Intellectual capital can be represented alongside physical assets in three distinct forms.

• Human Capital, such as knowledge, experience, and creativity of the company employees.

Structural Capital encompasses an organization’s capability to effectively execute its functions, including vital elements such as information resources, technological systems, industrial properties, and franchises It also reflects the corporate culture, process efficiency, service quality, and innovation capacity, all of which contribute to the overall performance and competitiveness of the organization.

• Relational Capital of the company with agents in its environment (customers, suppliers, government agencies, etc.), as well as the brand valuation, customer portfolio, relationships with them, etc.

Valuation methods for intellectual capital primarily involve summing various types of capital, adjusted by efficiency indexes Following the calculation method established by prior research, the assessment of an organization's intellectual capital is represented as the total of human, structural, and relational capital, each multiplied by their respective efficiency ratios.

CI ẳ i H CH ỵ i S CS ỵ i R CR ð11:3ị where

• CH, CS, and CR represent the economical value of human capital (CH), structural capital (CS), and relational capital (CR).

The efficiency indexes for intellectual capital are represented by i H, i S, and i R When multiple indexes exist for each type of capital, the overall efficiency is calculated using the arithmetic mean, expressed as [(i 1 + i 2 + + i n )/n].

Proposed Methodology

This section quantitatively demonstrates how implementing after-sales service management can enhance organizational value We will evaluate the effectiveness of technical assistance in terms of reliability, providing measurable insights into its impact.

Investing in human capital primarily involves expenditures on salaries and education or training From an accounting perspective, the effectiveness of these investments can be measured through specific performance indicators.

• Investment in salaries (CH salary ):

– Staff motivation (i H_motivation ) This indicator is the rate on personnel motivation.

– Staff performance (i H_performance ) This indicator represents the performance of the technicians.

– Task productivity (i H_productivity ) That means: [Task hours]/[total of hours]

• Investment in training (CH training ):

– Staff percentage covered by training plans (i H_training ).

– Staff percentage with skills to develop the assigned tasks (i H_skills ).

– Relationship between staff that perform work orders according to the standard number of hours and the total work orders (i H_efficiency ).

Human error probability (HEP) plays a crucial role in business reliability, particularly in stressful situations with time constraints and concerns, leading to potential errors that can have serious consequences It is essential to quantify the contribution of human capital to understand the true potential of staff Research indicates that human errors account for approximately 20 to 30% of failures in industrial assets, highlighting the significant impact of human factors across various sectors.

Human reliability analysis (HRA) often employs probabilistic risk assessment to evaluate human error probabilities (HEP) Higher HEP values indicate an increased likelihood of errors, leading to greater technical assistance costs The impact on intellectual capital can be quantified by multiplying the reliability factor by the average cost of technical assistance and the total number of assistance instances during the evaluation period, resulting in a significant negative contribution to overall performance.

Therefore, human capital must be reduced in relation to human errors, because it causes extra corrective activities. i H motivation þ i H performace þ i H producvity

3 CH salary þ i H training þ i H skills þ i H efficiency

Regarding customers and intellectual relational capital, companies invest in customer service (CR client ) so that the efficiency of the investment can be represented by the following indicators:

• The rate of customer satisfaction due to the received assistance service (i R_satisfaction ).

• The percentage of clients who are not affected by warranty incidents (i R_clients ).

That means: (1 - [sum of clients affected by failures/total sum of clients]).

Customer service plays a crucial role in shaping customer perception, as higher product reliability leads to fewer customer claims and a reduced need for technical support, ultimately enhancing customer satisfaction To effectively measure assistance quality, companies must assess various attributes, including technical support efficiency, response times, reliability, and safety However, gauging the quality perceived by customers remains challenging Service quality significantly impacts customer perception, with satisfaction levels rising when incidents are resolved promptly and effectively Thus, we will focus on two key criteria to evaluate the effects of assistance on service quality.

• A poor assistance causes more damage than a good assistance in the customer’s perception Client’s perception is diminished with a bad service quality and transmits negative product advertising to the market.

Determining the level of incidents that necessitate specific service standards is crucial, as it aligns with market benchmarks and the agreements established with clients.

Client behavior varies significantly, with some customers seeking monetary refunds while others may opt for legal action or simply cease purchasing our products Negative experiences can lead clients to share unfavorable feedback, often recalling these incidents at their convenience Each customer has a unique perception of service quality, which can be assessed through statistical methods like Survival Data Analysis, evaluating reactions over time Additionally, service quality can be measured by adherence to warranty agreements, delivery timelines, response and recovery times, and overall service accuracy Quality is deemed acceptable to customers when it falls within a defined tolerance level, represented by P a (t R ), indicating the probability of customer loss based on repair outcomes.

To effectively analyze loss average probability in a specific sector, one can leverage historical data from industrial assets introduced to the market Various techniques are available to conduct this type of analysis, allowing for a comprehensive understanding of potential risks and returns.

In various industries, the concept of "net present value of the customer" (NVC) is utilized to represent the updated profit generated per customer This figure reflects the total revenue earned from a client throughout their relationship with the company, after deducting direct sales costs, acquisition expenses, and retention discounts To assess the risk associated with customer loss, one must multiply the reliability factor (i R reliability) by NVC, the average number of customers impacted by incidents (n c), and the average number of failures (n f) This calculation provides a comprehensive view of the potential financial implications of customer attrition.

Therefore, the relational capital must be reduced in accordance with the probability of clients that can abandon the service, as shown in the following formula: i R satisfaction þ i R income ð ị

11.4.3 Generated Value Regarding the Company Structure

From an accounting perspective, the primary structural capital investments include expenditures on standardization, prevention, and performance assessment (CS process), as well as investments in information and communication technologies (ICT) and innovation (CS ICT) The effectiveness of these investments can be evaluated using specific performance indicators.

• Investment in standardization, prevention, and performance assessment (CS process ).

– Change in the planned activities (i S_planned ) That is, the relationship between planned assistance and total assistance.

– The capacity rate used in relationship to the maximum capacity in support services (i S_capacity ).

• Investment in ICT and innovation (CS ICT ).

– Percentage of staff that apply TICs (i S_personnel_ICT ).

– Percentage of industrial assets covered by ICT as tools for monitoring or forecasting (i S_equipment_ICT ).

Reliability plays a crucial role in maintaining the structural integrity of a company, serving as a key indicator of asset conservation It is essential to evaluate how reliability influences the overall company structure, as it directly impacts performance and sustainability.

A key metric for assessing asset performance is equipment availability, which is determined by the average Mean Time Between Failures (MTBF) of critical components and the average Mean Time to Repair (MTTR) In various industrial sectors, equipment availability (A_e) significantly influences total revenue due to potential customer loss The impact of asset unavailability can be quantified by multiplying the unavailability rate by the Net Value Contribution (NVC) and the total number of clients (n_c) This negative contribution ultimately affects the overall intellectual capital of the organization.

Therefore, the structural capital must be reduced in accordance with the product’s availability as can be seen in the following equation: i S planned þ i S capacity

2 CS process þ i S personnel ICT þ i S equipment ICT

2 CS ICT i S equipment availability NVC n c : ð11:9ị

It is important to note that the quantification of intellectual capital can vary by department or sector The methodology proposed is rooted in the doctoral thesis referenced in Ref [47] Additionally, we recommend reviewing the subsequent section, which addresses further aspects of intellectual capital quantification, complementing the concepts discussed here.

Case Study on the Intellectual Capital

This section presents a case study relevant to a water distribution company, focusing on the comparison of technical assistance services and intellectual capital between two similar companies Utilizing the formula outlined in Chapter 11, we will quantify the maturity of after-sales services, reflecting organizational capabilities This assessment, previously discussed in Chapter 6, emphasizes the importance of measuring management effectiveness and efficiency Ultimately, the evaluation of after-sales management will provide a quantitative value that highlights improvements in reliability and the quality of the water distribution service, guiding managers in their decision-making processes.

Understanding quality costs enables better decision-making and justifies investments in quality improvement, while simultaneously enhancing the efficiency of efforts made.

Investing in intellectual capital significantly enhances organizational value, with human reliability being a crucial factor in driving economic growth The proposed methodology facilitates the measurement of evolving norms and regulations, enabling effective comparisons with industry competitors.

External references are used as objectives in order to determine maturity [51,

Table 11.1 presents various indicators assessed in the study of different companies, as detailed in Ref [53] The evaluation methods for intellectual capital utilize key reference indicators, including personnel motivation, customer satisfaction, employee performance, training rates, the extent of TIC establishments, unplanned activities, and resource efficiency.

Table 11.1 International indicators indicadores internacionales

Yearly maintenance costs: Total maintenance cost/Total manufacturing cost \ 10–15 %

Maintenance cost/Replacement asset value of the plant

Hourly maintenance workers as a % of total 15 % Planned maintenance: Planned maintenance/Total maintenance [ 85 %

Scheduled maintenance as a % of hours worked *85–95 %

Run-to-fail (emergency ? non-emergency) \ 10 % Maintenance overtime: Maintenance overtime/Total company overtime \ 5 % Monthly maintenance rework: Work orders reworked/Total work orders *0 %

Inventory turns: Turns ration of spare parts [ 2–3

Training For at least 90 % of workers, hours/Year [ 80 h/year

Spending on worker training (% of Payroll) *4 % Safety performance: OSHA Recordable Injuries per 200,000 labor hours \ 2

Total hours PM/Total maintenance hours available *20 % Total hours PDM/Total maintenance hours available

Total hours PRM/Total maintenance hours available

Total hours REM/Total maintenance hours available

Total hours RNEM/Total maintenance hours *8 %Available time/Maximum available time [ 97 %Contractors Contractors cost/Total maintenance cost 35–64 %11.5 Case Study on the Intellectual Capital in Technical Services 253

It is essential to evaluate both the negative impacts of technical services and the positive outcomes derived from high-quality service, especially in key areas of intellectual capital.

• The human capital or related to personnel through personnel and human reliability investments.

• The relational capital referring to quality through investments in quality and consequences of customer satisfaction.

• The structural capital or company structure, through structural investments and equipment preservation.

To enhance customer satisfaction, distribution companies must align their performance indicators with key factors such as network reliability, availability, and restoration time, ensuring that the quality of service provided meets these essential criteria.

11.5.2 Results of the Practical Application

This article analyzes the contributions and impacts of after-sales services by comparing two water distribution companies operating in the same area over a specific time period.

Table 11.2 provides an overview of the applied investments and key performance indicators for companies A and B, both of which invest 900,000 €/year By utilizing the formulas from Chapter 11, we calculate the intellectual capital, revealing values of 695,417 for company A and 777,417 for company B, both of which fall below their respective investment amounts.

Likewise, the following details can be distinguished:

• There is more structural capital in company B than in A due to the ICTs inversion.

• There is more relational capital in company B than in A due to the fact that customer satisfaction is higher given that fewer customers are affected by the failures.

• The human capital is the same for both although company A is more efficient due to the motivation factor.

In addition, the impact of reliability is also assessed; these values will reduce the intellectual capital in terms of possible risks in the network to the results of Table 11.4.

Table 11.2 Applied inversions and main KPI’s

(b) Investment in learning and training 50,000 100,000

(d) Investment in quality and processes 300,000 250,000

(e) Investment in ICT and innovation 150,000 200,000

6 Fulfillment of efficiency versus standards 85 % 80 %

8 Customer incomes affected by failures 80 % 95 %

12 Equipments with ICT and optimization 80 % 80 %

Table 11.3 Application of the formulas to assess intellectual capital

Capitals equations Company A Company B a 9 average(1 ? 2 ? 3) 255,000 212,500 b 9 average(4 ? 5 ? 6) 44,167 86,667 c 9 average(7 ? 8) 77,500 90,000 d 9 average(9 ? 10) 202,500 206,250 e 9 average(11 ? 12) 116,250 175,000

11.5 Case Study on the Intellectual Capital in Technical Services 255

When assessing the effects of human errors, it is evident that company B experiences a greater negative impact on performance compared to company A This disparity arises from the higher Human Error Probability (HEP) in company B, despite both companies having similar average activity costs and the number of activities.

When the re-establishment time varies between two companies while maintaining the same CNVP, company A faces greater cost implications due to a higher likelihood of abandonment.

The reliability of equipment is significantly improved, particularly when considering a scenario where the equipment serves 200 customers With a CNVP of €3,000 per year, the adverse effects are more pronounced in scenario A compared to scenario B.

Table 11.5 illustrates a growing disparity between Company A and Company B, with Company B's value surpassing that of Company A This increase is primarily attributed to Company B's lower risk levels, including reduced human error and fewer network failures, despite both companies commencing with identical budgets This case study is further substantiated in the doctoral thesis [47].

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Table 11.4 Negative impact when applying reliability

Table 11.5 Result of intellectual capital and reliability impact

CI_human-impact of human reliability 277,079 274,429

CI_relational-impact on customers 54,100 81,000

CI_structural-impact on production 228,750 351,250

5 Murthy DNP, Atrens A, Eccleston JA 2002 Strategic maintenance management Journal of Quality in Maintenance Engineering 8(4):287-305.

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Boston, MA: Harvard Business School Press.

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29 American Accounting Association 1977 Report of the Committee on Human Resource Accounting.

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31 Stewart T 2001 The Wealth of Knowledge: Intellectual Capital and the Twenty-First Century Organization Nicholas Brealey.

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33 INTELECT 1998 Medición del Capital Intelectual: Modelo Intelect Euroforum Madrid.

34 Riesco GM 2007 El negocio es el conocimiento Ediciones Díaz de Santos.

35 Bley D 2002 New methods for Human Reliability Analysis Environmental Management &

36 Hollnagel E 2006 Human Reliability Analysis International encyclopaedia of ergonomics and human factors Karwowski Waldeman Taylor and Francis Group Pp 753-757.

37 Dhillon BS 1989 Human errors: a review Microelectron Reliability 29(3):299-304.

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39 Swain AD, Guttman HE 1983 Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications NUREG/CR-1278, USREG, Washington, DC.

40 Johnson RL, Tsiros M, Lancioni RA 1995 Measuring Service Quality: A System Approach.

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42 Cox DR, Oakes D 1984 Analysis of Survival Data London; Chapman and Hall.

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45 Blischke WR, Murthy DNP 2000 Reliability Modelling, Prediction and Optimization.

46 Harrell FE 2001 Regression Modelling strategies Springer.

47 Gómez JF 2010 Marco de referencia para la gestión y evaluación del mantenimiento de redes de distribución de servicios Tesis doctoral dirigida por Adolfo Crespo Márquez.

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53 Mitchell JS 2007 Physical Asset Management Handbook Fourth Edition Clarion Technical Publishers, Houston, 440 pages, ISBN 0-9717945-4-5.

Maintainability and the After-sales Service

This chapter outlines a process for determining the maintainability index of industrial assets that require customer service technical assistance Maintainability, as defined by the European Standard UNE-EN 13306:2010, refers to the ability of an item to be maintained or restored to perform its required function under specific conditions and established procedures It plays a crucial role in the dependability of industrial devices, which encompasses reliability, maintainability, and technical support To evaluate maintainability effectively, it is essential to describe the device's usage conditions, including operational methods, location, and environmental factors Additionally, understanding the device's structural characteristics, assembly, installation, and maintenance routines is necessary The analysis will also identify various levels of technical assistance and their corresponding procedures Furthermore, the evaluators must undergo training and accreditation in technical assistance and maintainability to ensure accurate assessments of maintainability indexes under different usage conditions and life cycle stages.

The evaluation of the maintainability index for the device is crucial for enhancing its design, ensuring it can support efficient warranty and maintenance services under various environmental conditions.

During the operational phase of a device, particularly within the warranty period, periodic evaluations of the maintainability index are crucial to assess the effectiveness of technical assistance under varying operating conditions It is vital to focus on the device's capabilities rather than the qualifications of the technical support organization When discussing maintainability attributes, such as the required training for technical support staff, the emphasis is on the necessary qualifications for performing specific technical tasks, not on the current training levels of the existing personnel Understanding this distinction is essential for accurately interpreting and applying the concepts outlined in this section.

Brief Review of the State of the Art

This section provides a brief overview of the primary methods for measuring technical assistance performance, rather than an exhaustive analysis The various contributions can be categorized into two main approaches based on the source and nature of the input information.

1 Expert methods: Those ones based on the use of the experience and knowledge of maintenance experts combined with historical data and objective assessments.

2 Statistical methods: Those ones based on the application of historical data recorded from trials.

12.1.2 Summary of the Reviewed Bibliography

In our review to the literature, the most referred contributions that we could find in this area have been the followings:

Eldon defines Mean Time to Repair (MTTR) as a key maintainability indicator, encompassing all repair-related durations, from fault detection to post-repair verification and reinstallation This MTTR is derived through statistical inference using historical data For complex devices, the overall MTTR can be calculated by aggregating the individual MTTR values of each component.

260 12 Maintainability and the After-sales Service

Houshyar [3] introduces a software tool designed for device operators, enabling them to record data that facilitates the calculation of performance and maintainability based on the collected information.

Sols [4] identifies various indicators that assess different facets of technical assistance operations related to maintainability, although it lacks a comprehensive overview These indicators are generated through statistical analyses of historical data.

For example, the probability that the repair time is below a certain time for certain operations (lognormal distribution), the average repair time to get up to

Ninety percent of equipment functions, man-hours dedicated to relief efforts, and the average cost of technical assistance are all key statistical parameters that reflect maintainability and provide valuable insights into this crucial index.

Wani [5] evaluates tribo-maintainability in mechanical devices through a tribological lens, utilizing a qualitative assessment table where experts assign numerical values to various tribology features This data is then processed through an algorithm to determine the overall tribo-maintainability.

The vector projection method (VPM), as proposed by Chen, utilizes a multi-objective evaluation approach that incorporates qualitative assessments with a weighted methodology to determine sustainability values This method categorizes factors into three main groups: physical design (including simplicity, accessibility, and assembly), logistical support (such as tools and documentation), and ergonomics (covering failure and operating indicators, as well as the skills of technical staff) Each factor is assigned a weight based on its significance in the overall evaluation.

• Smith [7], discusses the empirical U.S Military Handbook 472, whose proposal presents the mean time to repair as an important indicator for maintainability.

There are two primary methods for calculating Mean Time to Repair (MTTR) The first method involves determining the average repair time for each failure, while the second method assesses various maintainability factors that contribute to MTTR This second approach requires a detailed analysis of each failure using a comprehensive checklist.

The assessment involves 32 factors, categorized into 15 design elements, 7 logistical support aspects, and 10 personnel qualifications An expert evaluates the current status of requirements for each factor Ultimately, the aggregated points from these categories facilitate the calculation of mean time to repair, derived from a regression analysis of repair times.

Coulibaly identifies two primary indicators for maintainability: one considers the criticality of the device components, while the other does not These indicators focus on access and assembly time for all components Additionally, other significant metrics, such as Mean Time to Repair (MTTR) and its time components, play a crucial role in evaluating maintainability All calculations are derived from statistical data or simulations for new items lacking historical data.

• Guo [9] calculates MTTR from historical data and validate statistically the result Although MTTR is related to maintainability, the author makes no considerations about that.

12.1 Brief Review of the State of the Art 261

Ben Daya analyzes maintainability through a statistical lens, identifying key factors that affect the maintainability of industrial assets His research highlights the importance of staff skill requirements, working conditions, and the overall work environment He employs statistical methods to calculate maintainability indicators, including the maintainability function and the durability of technical assistance.

Liu emphasizes the importance of human factors in device maintainability during the design process, categorizing these factors into four key areas: maintenance operations safety, accessibility, comfort, and practicability.

Lu [12] introduces a procedure for expert-based assessment, focusing on various factors that influence maintainability, including identification, ergonomics, testability, simplicity, and other experience-based elements Each factor is evaluated using a verbal scale, which is then converted into numerical values through fuzzy logic.

Abas [13] employs statistical methods, utilizing Software Relex, to assess repair time in a case study This analysis incorporates various environmental and operational conditions alongside repair time data, aiming to enhance the understanding of maintainability through statistical indicators.

12.1.3 Conclusions of the Literature Review

There are two primary approaches to evaluating the maintainability and performance of technical assistance for systems or equipment: internal maintenance and customer service perspectives The first approach utilizes statistical methods that assess the probability of performing technical or maintenance tasks at specific times In contrast, the second approach relies on expert observations, considering factors such as the environment, logistics, and personnel training that influence after-sales service and maintenance effectiveness While some researchers explore complex mathematical models or graph theory, these methods are not widely adopted The expert-based method discussed here offers a practical and comprehensible way to achieve a thorough and up-to-date assessment of maintainability.

Definitions and Requirements for the Assessment

Maintainability refers to an item's ability to remain functional or be restored to functionality under specific usage conditions, provided that technical assistance is performed using established resources and procedures The maintainability index is a key metric for assessing this capability, evaluating either the overall maintainability of a component or its maintainability at a specific level of technical support This level of technical assistance encompasses a series of actions related to after-sales service, aimed at executing specified interventions that align with the warranty and maintenance requirements of the component.

The levels of intervention for an element are categorized as system, subsystem, and component, influenced by factors such as construction complexity, subsystem accessibility, after-sales service staff competence, availability of testing equipment, and security levels "Unavailability" refers to the time a product is unable to function as intended after it has been delivered to the customer, typically due to a failure or incapacity during preventive maintenance.

For comprehensive information, refer to the UNE-EN 13306:2010, which outlines maintenance terminology, and the UNE 20654:1992, which serves as a guide for maintainability requirements and programs The evaluation of maintainability indexes will depend on several criteria, including the evaluator's qualifications, the operational conditions, and the frequency of assessments conducted in the specific environment.

The person in charge of the assessment must demonstrate:

– An academic background in the maintenance field of at least 100 h;

– A 25 h academic training in the maintainability field and after-sales area.

To assess the maintainability index of a device in its operational phase, it is essential that operators and technicians are readily available to provide clarification to the evaluator regarding technical assistance procedures Additionally, the operating conditions and environment of the device during the maintainability evaluation must be thoroughly documented and described in detail to ensure accurate results.

• Requirements for the assessment frequency

In order to achieve continuous improvement of maintainability index, it would be desirable periodical evaluations, depending on the level of activity to be

12.2 Definitions and Requirements for the Assessment 263

The evaluation of the device registered at the facilities is crucial, especially when significant changes in the environment or usage conditions are anticipated This assessment will help analyze the implications for technical assistance effectively.

Maintainability Indicators and Maintenance

The maintainability indicators are assessed according to two kinds of attributes or characteristics of the device:

• General attributes: Those affecting any device maintenance level That is to say, they are maintenance level independent.

• Specific attributes: Those depending on the maintenance level That means, they are functions of all the maintenance actions to be performed on a specified maintenance indenture level.

The assessment of maintainability attributes for a device involves classifying maintenance actions into five specific levels This paper evaluates the maintainability performance at each level, ensuring that the relevant attributes are considered in the development of maintenance actions A five-point scale from 0 to 4 is used to rank these attributes, minimizing subjectivity for easier interpretation The maintenance levels are determined based on the complexity of tasks and the resources required, including the necessary unavailability time of the device These levels adhere to globally accepted criteria.

Level 1 maintenance involves straightforward actions conducted while the device is operational Operators carry out preventive or corrective tasks that do not necessitate shutting down the device, such as making simple manufacturer-recommended adjustments or replacing easily accessible components.

Level 2 maintenance involves replacing functional components, which temporarily puts the device into a down state During this time, operators conduct preventive and corrective maintenance, focusing on the essential components of the device that require replacement.

• Level 3: Failures identification and diagnosis In these maintenance actions the operator, after setting the device into a down state, identifies and locates the causes of the failures.

Level 4 inspections involve comprehensive testing and maintenance actions, which may necessitate the complete or partial disassembly of the device These inspections are crucial for ensuring the device maintains its required availability and safety over time Typically, revisions are conducted at specified intervals or after a predetermined number of operations.

Level 5 encompasses updating, reconstruction, and overhaul processes, which fall under the maintenance responsibilities of the plant or manufacturer These crucial operations may involve modifications and improvements, potentially extending the lifespan of the original device.

Classification of the Maintainability Attributes

The assessment of maintainability indicators should consider device attributes, which are categorized into three groups: design-related attributes, work condition and staff requirement attributes, and logistic support needs It is crucial to understand how these attributes relate to the capabilities of the device being evaluated, rather than the existing maintenance organization's capabilities.

12.4.1 Attributes Related to the Device Design

Inside this group, we consider eight attributes:

• Simplicity: Existing reduction in the amount of elements and unnecessary assemblies.

• Identification: Clear location and signs from those components that are going to be mainly maintained, and from those existing points for inspection and test.

Modular device design allows for the creation of separate functional assembly units, enabling targeted repairs without the need to disassemble the entire equipment This approach simplifies maintenance by allowing users to address only the specific part where a failure has occurred, enhancing efficiency and reducing downtime.

• Tribology: Right use of materials with appropriated quality in order to increase the use of life of fragile elements and to improve the lubrication of pieces wearing out quickly.

Standardization ensures that spare parts are compatible with similar materials when replacing device components This compatibility is influenced by the standards selected during the design process of elements like bearings and gaskets, as well as their dimensional and functional tolerances.

12.3 Maintainability Indicators and Maintenance Levels Description 265

• Failure watch: Indications in the device about critical parameters and alarms to foresee failures.

• Accessibility: Schedule for accesses to all those elements to be maintained through gates, sliding doors, etc.

• Assembly/disassembly: Easiness to remove or replace elements in the different subsystems This easiness shall be emphasized by gaskets, joints, welding etc. influencing also the elements size and volume.

12.4.2 Attributes Related to the Maintenance Staff and Work

Inside this group, we consider three attributes:

Ergonomics plays a crucial role in establishing optimal working conditions for maintenance activities by evaluating space requirements This aspect also considers the necessary locations and areas for placing materials, ensuring efficient interventions on the physical system.

• Training: Skill required to the maintenance staff for the kind of work to perform.

• Environment: Requirements on the environmental conditions are referred in order to enable the maintenance under proper conditions and complete safety.

12.4.3 Attributes Related to the Necessity of Logistics

Inside this group, we consider five attributes:

Effective collaboration with the manufacturer is essential for optimal plant maintenance Key requirements include establishing a common language, utilizing a unified system for machine management, addressing geographical remoteness, aligning working hours, and ensuring adherence to the same jurisdiction These factors facilitate seamless communication and coordination between maintenance personnel and the manufacturer, ultimately enhancing operational efficiency.

• Personnel organization: Amount of people required to carry out the maintenance operation and possibilities of dividing the work into parallel tasks.

• Spare parts: Requirements in terms of spare parts for their use in the maintenance activity where the acquisition easiness shall be observed.

• Maintenance tools and equipments: Requirements in terms of tools and instruments for performing the maintenance activity Functionality, ergonomics as well as the acquisition easiness will be observed.

• Interdepartmental coordination: Complexity in the task environment:

Requirements for handling of hazardous parts or elements, for the permit application, for the communication among different departments, etc.

• Documentation: Indications given by the manufacturer for the device maintenance or prepared for the maintenance service, explaining how to perform the maintenance action.

Maintainability Attributes and Maintenance Level

The 17 attributes, commented in the paragraph above, are grouped in two sets, according to Sect 12.4 The first group concerns those attributes that make influence on the device maintainability at any maintenance levels (General attributes); that is, a type of maintainability that is independent of the maintenance level The second group of attributes could influence the device maintainability in a different way and degree, deepening on the level of maintenance that is being considered (Specific attributes).

12.5.1 General Attributes and Their Assessment

There are eight key attributes that are independent of maintenance levels, and each is assessed individually by experts The evaluation yields an integer score ranging from 0 to 4 Below are some examples illustrating this assessment process.

G1 Simplicity: It will be checked for the use of a minimal amount of components and assemblies in the devices, even those components that are redundant.

• 0: Very high number of components with redundant elements, easily visible.

• 4: Optimized, reduced, and without redundancy number of components.

In the identification phase, it is crucial to ensure that all elements requiring maintenance and testing points are clearly marked Additionally, attention will be given to the identification of connectors and hazardous areas, as well as specific locations where technicians need to position themselves for safe and effective work.

• 4: Complete identification, everything can be seen in front of the device.

Standardization ensures that replaceable components are compatible with readily available market alternatives, leading to reduced storage needs and minimal adjustments throughout their lifecycle.

• 0: Very bad standardization High difficulty to find a spare part in the market.

High need of spare parts storage.

• 4: Good standardization High easiness to find spare parts in the market and with competitive prices There is no need to store spare parts.

12.4 Classification of the Maintainability Attributes 267

12.5.2 Specific Attributes (Maintenance Level Dependent) and Their Assessment

In device maintenance, particularly at the advanced levels, attributes may be evaluated in locations different from the device's usual setting An expert assesses nine key maintainability attributes at each maintenance level, assigning integer values from 0 to 4 Two specific attributes are highlighted as examples in Tables 12.1 and 12.2.

There are similar tables for other seven specific attributes (they are nine in total).

Table 12.1 Accessibility Level Watching this attribute will have as a target Assessment scale

1 Checking the proper access for first maintenance level tasks, for instance: basic inspections, consumable changes

2 Checking the proper access for second maintenance level tasks, easy repairs by replacement of functional elements, etc.

Ensuring appropriate access for third-level maintenance tasks is crucial for effective diagnosis and troubleshooting of device failures, as well as for the replacement or repair of minor components.

0: Very difficult access, it is needed to move things and the technician himself, etc.

4 Checking the proper access for forth maintenance level tasks, which involve important revisions on the device, test performances, etc.

5 Checking the proper access in order to perform reconstructions, updating or overhauls in the device

Table 12.2 Assembly/Disassembly Level Watching this attribute will have as a target Assessment scale

1 Checking the easiness for the assembly/ disassembly (open, close, connect, disconnect, adjust, etc.) of those subsystems or elements which are involved in the device of first maintenance level tasks

In the range [0–4], where: 0: Many difficulties: Many tools are needed.

Material weight, volume, and size are too important 4: Very easy to assemble and disassemble

Maintainability Indicators Assessment

In order to apply this methodology, it is required to calculate six indicators, based on the value of the attributes assessed at general level and at each maintenance level:

• One general maintainability indicator (GMI), which results from the device general attributes assessment.

• Five specific maintainability indicators, one for each maintenance level, named

‘‘maintainability indicator of maintenance level i’’ (where ‘‘i’’ takes the integer value 1–5) or LMI i , as a result of assessing the specific attributes of the device.

The maintainability of industrial assets is assessed through scores across eight general and nine specific attributes, totaling 45 values based on five maintenance levels However, managing this extensive data can be impractical for effective comparisons, and the significance of each attribute may vary for specific devices.

The importance of specific attributes can vary significantly based on the operating conditions of an asset, making some attributes crucial in certain scenarios while negligible in others To effectively manage the vast amount of heterogeneous information regarding asset maintainability, it is beneficial to consolidate this data into a few key indicators, reserving detailed attribute information for in-depth analysis Additionally, it is essential to evaluate the relevance of each attribute, which involves considering both the score of the attribute and its relative importance within the overall set This dual assessment complicates the analysis due to the increased complexity of handling extensive information Therefore, aggregating this data becomes imperative, and maintainability indicators should be calculated using a weighted average of the assessed attribute values to ensure a comprehensive understanding of asset performance.

In this analysis, we define \( p A_i \) as belonging to the set \{0, 1\}, where the sum of \( p A_i \) across all \( n \) attributes equals 1, indicating the relative weight of each attribute \( A_i \) This approach is similarly applied to general attributes \( G_i \) and specific attributes \( S_i \) in relation to their maintenance levels, with \( i \) representing the ordinal number of each attribute.

The calculation of the maintainability indicator involves a specific number of attributes: eight general attributes for the overall maintainability indicator and nine specific attributes for maintainability indicators at various maintenance levels.

To determine the contribution of each attribute to the maintainability indicator, we suggest the following procedure:

To evaluate the maintainability of a device, it is crucial to assess the significance of each attribute, represented as p A i = {0, 4} Experts must determine the importance of both general and specific attributes related to maintenance levels, considering the operational conditions of the device in question.

• The weight of each attribute (relative importance of each attribute within the set of them), will be: p A i ẳ P A i

P n iẳ1 P A i ð12:1ị The general maintainability indicator is defined as follows:

G i p G i ð12:2ị where i Ordinal number of each of the eight maintainability general attributes;

In the context of maintainability performance, each of the eight general attributes is assigned an integer value, G i, ranging from 0 to 4, reflecting their significance Additionally, a decimal value, p G i, is allocated to each attribute, ranging from 0 to 1, representing its weight These weights are derived from prior calculations, emphasizing the importance of each attribute in enhancing overall maintainability.

The maintainability indicator of maintenance level j is defined as follows:

S ij p S ij with j ẳ 1; 5 ð12:3ị where j Ordinal number of each of the five maintenance levels; i Ordinal number of each of the nine maintainability specific attributes;

The maintainability of a system is evaluated using an integer value, S_ij, which ranges from 0 to 4, representing each of the nine specific attributes across five maintenance levels Additionally, a decimal value, p_S_ij, is assigned to each attribute, reflecting its weight within the range of 0 to 1 for the same maintenance levels.

These weights have been previously calculated [Eq (12.1)], in a similar way to what we did for the case of GMI (Fig 12.1).

Finally, it should be underlined here that many of the considerations made in this section have inspired the Spanish Norm Project PNE 151001 of AEN/CTN

151 ‘‘Maintenance’’ of AENOR [15] Apart from this, as a continuation of Chap.

12, it is suggested to consult next section that deals with aspects of quantification of maintainability focused on what was here developed.

Case Study on Maintainability

This chapter presents a case study that illustrates the maintainability index through a practical application involving a bridge-crane, as depicted in Fig 12.1 The guidelines outlined in the previous chapter are utilized to analyze this industrial asset effectively.

The maintainability index of this industrial asset will be evaluated using assessment sheets, incorporating various global attributes and variables across levels 0 to 4.

The application scenario focuses on an industrial asset, specifically a bridge crane This bridge crane consists of a main car equipped with an engine for longitudinal movement along primary cranes, a secondary car with an engine for transverse movement on installed cranes, and an engine for the vertical movement of a hoist carrying a transportation hook.

(22, 31, 42) controlled by means of activation (24, 32, 43) that are characterized by having two radio receptors (51a, 51b) associated to a remote control (operated by radio) (52) to control the means of activation (24, 32, 43) of the engines (22, 31,

42) in a wireless fashion; this is because the radio receptor (51a) is located in the

Fig 12.1 Graphical representation of general maintainability indicator

The main car operates the engine activation system to facilitate its movement, while the secondary car's engine is activated via a radio receptor located in the secondary car itself Additionally, the hoist's engine is also engaged to assist in the displacement of both cars.

This bridge crane features longitudinal cranes and a main car that incorporate electrified tracks interconnected by a power supply This setup powers the activation mechanisms for the engines, which are linked to radio receivers, ensuring efficient operation and control.

12.7.2 Application of the Evaluation Sheets

After outlining the scenario, we will analyze the evaluation sheets presented in Tables 12.3 to 12.8, along with their corresponding graphics illustrated in Figures 12.3 to 12.7, using the methodology established in Chapter 12.

Fig 12.2 Components of the bridge-crane

Table 12.3 Evaluation sheet of general attributes

Code Attribute Criteria Scale [0–4] where Value

G1 Simplicity It will check the utilization of a minimum number of components and groups in the devices, even those that are redundant

0: High amount of duplicated components, easily visible

G2 Identification ensures that all elements requiring maintenance and the associated testing locations are accurately identified, including connectors, hazardous areas, and specific work sites.

0: No identification 2 4: Perfect identification of equipment

G3 Modularization It will check that there are different functional units of assembly in the device, which would allow minimizing handling in case of maintenance intervention

0: Complex change of units and requires the movement of other units

G4 Tribology It will check that the correct material is selected for components which are subjected to friction, lubrication and wear, with the aim of maximizing their useful life

0: 0–10 % of the items are properly selected

4: 80–100 % of the items are properly selected

G5 Ergonomy evaluates the ease of maintenance tasks by analyzing the weight, size, and shape of the components involved It also assesses the work environments to ensure they are suitable in terms of lighting, space, and other factors, facilitating smooth and efficient task execution.

0: Tasks with complex implementation Elements are not comfortably handled because of their weight, size and shape, making the operator become tired Inadequate work space

4: Excellently ergonomic device, service is comfortable and agile

Code Attribute Criteria Scale [0–4] where Value

G6 Standardization It will check the compatibility of the components to be replaced with others that are available in the market.

This will equally benefit minimizing the storage of components and the minimum number of adjustments especially in replaceable elements in low levels of maintenance

0: Poor standardization High difficulty in obtaining spare parts in the market High necessity of storage for spare parts

4: Good standardization Easy to find replacements in the market at competitive prices No need for spare part storage

G7 Diagnosticability It will prove the existence of failure indicators in the device and the possibility to monitor those useful parameters for technical service

There are no indicators of the condition of equipment and it is impossible to make a diagnosis of its condition

Key indicators provide real-time data on equipment condition, allowing for easy monitoring Effective G8 coordination is crucial in developing maintenance tasks, highlighting the need for streamlined communication and management processes that align with other departments.

0: Poor coordination The technician is far away, speaks another language, etc.

4: Good coordination The technician is nearby, speaks the same language, there are no communication problems, uses standard technologies, etc.

12.7.2.2 Variables for a Level 0 Technical Assistance

Table 12.4 Evaluation sheet for variables of Level 0 for technical assistance

Code Attributes Criteria Scale Value

V1 Accessibility -Hinges 0: Very difficult access 5

-Doors 1: Incredibly difficult access -Removable shelves 2: Difficult access

3: Normal access 4: Very good access V2 Assembly/ disassembly

-Edge connectors 4: Very good manipulation V3 Personnel -Trained people according to the type of work

2: Too bad 3: Regular 4: Good V4 Technical equipment

-Number of people for technical operation

-Exhaust detection system 1: Dangerous -Presence of high tension cables

3: Safe 4: Very safe V6 Tools and equipment for technical assistance

-Weight and volume components for an easy handling

1: Many things 2: Too many things 3: Few things 4: Too few things

Code Attributes Criteria Scale Value

V7 Complexity of the technical assistance

-Possibility of simultaneous maintenance work

-Permits to carry out operations

4: Very well organized V8 Documentation -Convenient instruction and procedure manual for technical assistance

Table 12.5 Evaluation sheet of variables of Level 1 for technical assistance

Code Attribute Criteria Scale Value

2: Too bad 3: Regular 4: Good V4 Technical equipment

-Number of people for technical assistance

1: 4/5 people -Preventing active maintenance time

1: Many things 2: Too many things 3: Few things 4: Too few things V7 Complexity of the technical assistance

-Edge connectors 4: Very good manipulation

V3 Personnel -Trained people according to the type of work

2: Too bad 3: Regular 4: Good V4 Technical equipment assistance

V8 Documentation -Convenient instruction and procedure manual for technical assistance

-Connections 3: Good manipulation -Edge connectors 4: Very good manipulation V3 Personnel -Trained people according to the type of work

V6 Tools and equipment for technical assistance

Fig 12.3 Graph of maintainability index of Level 0

Table 12.9 summarizes the results derived from the various methodologies, while Fig 12.8 illustrates the overall index of the analyzed bridge-crane Additional relevant references can be found in sources [12, 13].

1 European standard 2010 EN 13306: Maintenance – Maintenance terminology CEN/TC 319.

2 Eldon CG 1990 An Analytic Approach to Performing a Maintainability Demonstration.

3 Houshyar A, Ghahramani B 1997 A practical reliability and maintainability data collection and processing software Computers & Industrial Engineering 33(1-2):133-136.

The results summarized in Table 12.9 highlight key attributes of the system Firstly, simplicity is achieved through a limited number of optimized components Secondly, all elements, including the pulley, engine, and weighting system, are clearly identified, with the exception of the crane's maneuver frame Thirdly, the modularity of the design allows for easy separation of different functional units Lastly, while the bearings are lubricated, there is noticeable wear on the rails, and the grease used is inadequate for the cables, with cable temperature not being considered in the lubrication assessment.

G5 Ergonomic Weight and size of the components is reasonable G6 Standardization Hooks, cables, and devices limit the load G7 Diagnostic ability

There are too many failure indicators and the possibility of parameter monitor is useful for technical assistance

G8 Coordination There is a good coordination: situation, language, and technologies

Fig 12.8 Graph of general attributes

4 Sols A 2000 Fiabilidad, Mantenibilidad, efectividad: un enfoque sistemático Madrid:

5 Wani MF, Gandhi OP 2002 Maintainability design and evaluation of mechanical systems based on tribology Reliability Engineering & System Safety, 77(2):181-188.

6 Chen L, Cai J 2003 Using Vector Projection Method to evaluate maintainability of mechanical system in design review Reliability Engineering & System Safety 81(2):147- 154.

7 Smith DJ 2005 Reliability, maintainability and risk: practical methods for engineers.

8 Coulibaly A, Houssin R, Mutel B 2008 Maintainability and safety indicators at design stage for mechanical products Computers in Industry 59(5):438-449.

9 Guo B, Jiang P, Xing YY 2008 A Censored Sequential Posterior Odd Test (SPOT) Method for Verification of the Mean Time To Repair IEEE Tansactions on Reliability 57:2.

10 Ben-Daya M, Duffuaa SO, Raouf A, Knezevic J, Ait-Kadi D 2009 Handbook of Maintenance Management and Engineering London: Springer-Verlag London.

11 Liu R, Lv C, Zou Y, Zhou D 2009 The preliminary study on the human-factor evaluation system for maintainability design International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2, art 5336031, pp 107-112.

12 Lu Z, Sun YC 2009 Maintainability virtual evaluation method based on fuzzy multiple attribute decision making theory for civil aircraft system Proceedings of 2009 8th International Conference on Reliability, Maintainability and Safety, ICRMS art 5270100, pp 684-689.

13 Abbas B, Javad B, Tore M 2011 Maintainability analysis considering time-dependent and time-independent covariates Reliability Engineering and System Safety 96:210–217

14 UNE 20654:1992 Maintainability requirements AENOR, Madrid

15 Proyecto de Norma Espaủola 2011 PNE 151001 del AEN/CTN 151 Mantenimiento.

16 Carriún J 2008 Patente Espaủola solicitada por Motorman radio sistemas y aplicaciones, S.L Clasificación PCT: B66C13/22 Fecha de Concesión: 17/09/2008

Dynamic Modeling and Bayesian Networks in the After-sales Service

In today's advanced markets, customers increasingly seek complex products and integrated services, known as product-service systems (PSS), which enhance the value of industrial assets Companies are now expected to provide comprehensive after-sales services, including maintenance, spare parts supply, and warranty extensions, alongside their products This chapter explores how continuous simulation can improve decision-making in this PSS context, particularly through a dynamic system model that evaluates the impact of preventive maintenance contracts on the performance of agricultural machinery services Additionally, we will investigate a novel approach to after-sales service focused on the end-of-life phase of products, employing Bayesian network theory to develop an optimal disassembly plan for complex industrial assets This trajectory model will address key factors and uncertainties in the disassembly process, enabling managers to make informed decisions and assess the economic implications of various strategies, including warranty costs related to recycled products.

This chapter highlights the significance of analyzing various gathered results while also presenting innovative future approaches to after-sales management analysis.

Dynamic Systems Modeling

System modeling has traditionally relied on mathematical models to predict behavior based on specific parameters and initial conditions However, due to the complexity of most systems, analytical solutions are often limited, necessitating the use of computer simulation models These simulation models create a diverse array of scenarios for a given model, encompassing all possible conditions, including those that may be considered forbidden or impossible.

To effectively navigate the complexity of multifaceted and dynamic structures involved in the provision of Product-Service Systems (PSS), a robust modeling tool is essential for designing improved operational policies and guiding necessary changes This research adopts a dynamic systems approach, which is particularly suitable for complex systems and adept at addressing issues related to continuous processes characterized by nonlinear behavior and extensive feedback Utilizing dynamic system modeling and discrete event simulation can significantly enhance the understanding of business decision-making within the company.

The primary goal of dynamic systems is to utilize quantitative models to comprehend system behavior and forecast the consequences of policy changes on system performance In contrast, discrete event simulation typically focuses on specific processes rather than entire systems, exceling at providing in-depth analysis of systems involved in linear processes and discrete models, thereby offering a more detailed understanding of their dynamics.

Therefore, given the potential of dynamic systems, the model presented in this chapter has been developed to:

1 Comprehend and represent, through the study of connections between service indicators, the nonlineal relations of all involved processes in the provision of a PSS.

2 Evaluate in a quantitative way, how the introduction of new policies for the PSS management significantly affects the company’s efficient performance.

3 Allocate appropriate organizational changes to the processes, thanks to the responses (feedback) that the simulation sets out with respect to the changes provided by the provision of the service.

The implementation of a new policy necessitates alterations in the external parameters that validate the dynamic system model, typically provided by the company being analyzed.

This model focuses on two key types of Product-Service Systems (PSS): maintenance services and spare parts supply Illustrated in Figure 13.1, it outlines the essential components and the logic used to develop a dynamic system model.

The dynamic system model has been developed following a general structure and can be used by any company that deals with PSS (especially maintenance and

286 13 Dynamic Modeling and Bayesian Networks in the After-sales Service

This chapter explores the impact of a new policy on after-sales service performance, particularly in the supply of spare parts To demonstrate the model's potential, a specific application within an agricultural sector company is proposed.

Case of Dynamic Modeling in the Farm

This case study focuses on a leading global manufacturer of agricultural machinery, particularly in the production, sales, and repair of harvesters The primary goal is to enhance after-sales processes to boost profitability and ensure customer retention, thereby securing future sales After-sales services include providing spare parts and maintenance, which are crucial for minimizing downtime during harvest season Quick repair assistance is essential for customers, making it imperative for the company and its authorized service centers to meet these demands effectively.

To minimize unexpected corrective repairs during the critical harvest season, the company has adopted a new strategy aimed at reducing maintenance interventions.

PROCESSES INVOLVED IN THE PSS PROVISION

SPARE PARTS DEMAND FORECASTING MANAGEMENT

Fig 13.1 Logic behind the construction of a dynamic system

To enhance after-sales support, it is essential to implement maintenance actions more frequently Maintenance can be defined as a series of necessary tasks aimed at ensuring optimal performance and longevity of products.

1 To control the deterioration process that leads to a failure in the system and,

2 To restore the system to its operative condition through preventive actions after a failure.

Preventive maintenance focuses on proactive measures to avoid system failures, while corrective maintenance involves unplanned actions to restore a malfunctioning system to operational status This process includes repairing or replacing defective components to ensure optimal performance.

Preventive maintenance is strategically scheduled to minimize the risk of equipment failure and to prolong the lifespan of components While implementing these regular maintenance activities may incur higher costs for users compared to waiting until repairs are essential, the long-term benefits of reduced downtime and extended equipment life often outweigh the initial expenses.

Comparing costs and long-term benefits of preventive maintenance is crucial, as it can lead to savings through reduced system downtime, better spare parts management, and increased reliability For sellers, preventive maintenance is vital during the warranty period since buyers typically cover these costs, thereby minimizing the seller's expenses related to corrective maintenance Conversely, buyers who overlook the importance of investing in preventive maintenance during the warranty period end up shouldering the full maintenance costs throughout the asset's lifespan This lack of incentive for sellers to invest in preventive maintenance is evident, as buyers do not pay for repairs during warranties, leaving sellers to rely on potential benefits like customer loyalty to justify the costs.

Both sellers and buyers should carefully assess the pros and cons of entering into a service contract that offers warranty extensions, preventive maintenance, and corrective services To address these considerations, the simulation of dynamic systems can provide valuable insights and answers.

This analysis evaluates the impact of preventive maintenance contracts on the after-sales service performance of the company, focusing on three distinct scenarios.

288 13 Dynamic Modeling and Bayesian Networks in the After-sales Service

• Escenario Scenario A: There is no preventive maintenance contracts applied, either in or out of warranty;

• Escenario Scenario B: Preventive maintenance contracts are acquired by customers just under a warranty period;

• Escenario Scenario C: Preventive maintenance contracts are acquired during the product’s whole life cycle, in or out the warranty period.

The analysis conducted from the seller's perspective (manufacturer) encompasses the entire life cycle of the product The model is initiated based on the current installed base within the company and simulates a monthly period over 30 years to evaluate the complete life cycle of a harvester, typically lasting 15 to 20 years Key assumptions have underpinned the model's framework.

• Each time a failure occurs, it is due to the incorrect operation of a component, and it occurs in all equipment in the market;

• Only one type of replace pieces is considered (in this case in concrete: the rotor);

• The failure rate of spare parts has been estimated as constant and is produced after a certain number of worked hours (or bales produced);

Customers can secure a preventive maintenance contract that covers the costs of maintenance interventions and any necessary spare parts, regardless of whether they are within or outside the warranty period.

• Preventive actions are cyclic, they are carried out at predetermined time intervals;

• Preventive and corrective interventions are carried out assuming that the component is restored to a good condition such ‘‘as good as new’’.

To implement the dynamic model system, exogenous parameters have been incorporated, including equipment demand, a one-year warranty period, preventive intervention cycle time, product failure rate, and costs associated with preventive and corrective interventions Additionally, the unit costs for personnel and spare parts inventory have been supplied by the company.

Following all this, these charts show the main obtained results through a simulation Figure 13.2 shows the high-level diagram of the modeling.

Implementing preventive maintenance contracts yields significant advantages for the company, as increased frequency of preventive maintenance correlates with enhanced benefits from after-sales services.

Limiting preventive maintenance to the warranty period is less advantageous than extending it throughout the entire lifecycle of harvesters Continuing with the same maintenance strategy post-warranty can lead to increased operational costs for the company.

To effectively implement both preventive and corrective interventions, an increase in personnel is necessary, which is justified by the long-term benefits gained throughout the product's life cycle Additionally, regular preventive maintenance significantly reduces the uncertainty surrounding spare parts requirements, leading to a decrease in orders This trend is visually represented in the evolution of accumulated costs for spare parts throughout the product's life cycle.

The tendency of costs is influenced by personnel inactivity that accumulates over the product's lifespan Unlike corrective maintenance, maintenance interventions are scheduled regularly, allowing for better planning and optimization of technical staff work time.

Results and Conclusions

Summary of Results of this Work and Research

Chapter 2 establishes a study scenario that effectively summarizes the business process of warranty management The analysis reveals that leveraging information from after-sales and recollection services throughout the lifecycle of an industrial asset can significantly enhance decision-making, ultimately leading to reduced unnecessary costs and improved service quality This strategic use of data not only elevates the overall customer experience but also strengthens the business's reputation.

In today's business landscape, software tools play a crucial role in automating selections and simulating processes to identify weaknesses Chapter 3 summarizes key contributions related to warranty management, information gathering, and best practices from various authors This analysis outlines essential steps for establishing a modern and efficient management framework, demonstrating how strategic service management can reduce the additional costs associated with technical assistance To effectively manage after-sales costs, businesses must understand the extent of these costs, clearly define warranty services, and provide detailed specifications for accurate cost estimations.

14.1.2 Methodology and Resolution Proposal (Part III)

The evolution of advanced technologies in manufacturing has significantly transformed production contexts, enabling companies to produce customized products at scale However, this shift towards greater automation and reduced inventories has heightened the pressure on maintenance systems To address this challenge, various maintenance management models have been developed, aimed at alleviating this pressure and aligning with industry needs Some organizations seek operational guidance to meet their maintenance objectives, while others focus on creating automated systems or evaluating maintenance functions Central to these efforts is the continuous improvement of performance, guided by a new model that adheres to the standards of ISO 9001:2008.

• It is open to the rest of organizational functions.

• Clearly distinguishes the execution of strategic and operative actions, when these appeared linked.

• Standardizes evaluation, control, and improvement in efficiency and effectiveness of maintenance.

• Contributes to the generation of documents and records for decision-making.

304 14 Summary of Results and Conclusions

• It is orientated in compliance with a quality management system.

Chapter 5 proposes a comprehensive framework essential for managing technical assistance services, focusing on improving organization and decision-making This framework classifies existing techniques based on their optimal application within warranty management, aiming to address challenges in the after-sales sector while incorporating modern business management trends, including the use of ICTs The chapter offers an updated overview of vital methods, technologies, and techniques that empower organizations to navigate the complexities of after-sales management in both manufacturing and services Chapter 6 further explores standards, best practices, and maturity quantification, emphasizing the significance of quality in after-sales management It highlights the necessity for management to ensure that industrial assets fulfill their intended purposes and advocates for a proactive approach to quality management that prioritizes customer satisfaction and minimizes costs associated with error correction Effective after-sales management must span the entire product lifecycle, requiring a strategic alignment of technical and commercial objectives to achieve overall organizational goals Additionally, the integration of established techniques from other fields can enhance after-sales practices by considering the interactions within the organizational framework.

14.1.3 Development of the Proposed Stages (Part IV)

Manufacturers are contractually obligated to provide warranty assistance to customers for sold products To achieve cost reduction and enhance product reliability, companies must make strategic, global decisions Additionally, offering effective after-sales service is crucial for customer satisfaction Implementing a balanced scorecard is vital for aligning local after-sales services with the overall objectives of the company.

14.1 Summary of Results of this Work and Research 305

Chapter 7 introduces the Analytic Hierarchic Process, a valuable methodology for making complex decisions by incorporating multiple levels of criteria and sub-criteria This versatile process can be effectively utilized in various contexts, including strategic planning, resource allocation, and business policy selection.

Finally, this chapter includes a root cause failure analysis study comparing in respect to a set of criterion, diverse tools commonly used in these analysis and observing their advantages and disadvantages.

Chapter 8 highlights the importance of efficiency in enhancing after-sales management services, emphasizing the role of Integrated Logistic Support in improving decision-making for complex component selection It also addresses key concepts such as task frequency and various repair levels, alongside critical analyses of risks, costs, and profits related to after-sales efficiency By applying project management theories to after-sales services as a defined project with a budget and milestones, these methodologies enable better control of warranty program progression, anticipation of additional expenses, and proactive decision-making, ultimately leading to increased customer satisfaction with both the company and its products.

Assessment and control procedures aim to establish a foundational understanding of the behavior of equipment components while extending this analysis throughout the industrial asset's life cycle As the design process evolves and market experience is gained, the initial values can be refined and adjusted, leading to more accurate insights and conclusions about the systems involved.

Chapter 9 introduces a formula for Reliability, Availability, Maintainability, and Safety, enabling the estimation of failure frequencies and guiding the scheduling of periodic revisions This analysis also aids in creating an initial list of recommended spare parts Additionally, products with longer warranty periods are perceived as more reliable and durable, making warranty duration a powerful marketing strategy for competing companies The chapter emphasizes the importance of the product life cycle in these considerations.

The analysis of costs, particularly in the context of repair studies, has led to the development of a formulation utilizing the non-homogeneous Poisson process (NHPP) and general renewal process (GRP) Implementing various methodologies for Life Cycle Cost Analysis (LCCA) can enhance decision-making processes, especially regarding after-sales services.

The application of stochastic models enables the prediction of potential product failures and the anticipation of associated repair costs, aiding in post-launch product management The Non-Homogeneous Poisson Process (NHPP) effectively estimates warranty period costs due to the variable failure rate and operational time, indicating that these factors are not uniform Conversely, the General Repair Process (GRP) is recommended for improved accuracy, particularly in managing complex repairs.

Chapter 10 observes distinct aspects of Application of ICTs in reference to a specific case of warranty management process These technologies can facilitate and improve the decision-making process In regard to after-sales services, these decisions can be, for example, the possibility to forecast failures in the product and in this way anticipate eventual customer reclamations Currently, ICTs are being applied in various fields That is why, the intention of this research to focus these electronic technologies to a new and emerging concept in electronic warranty, in a similar way to the already consolidated term e-maintenance In a few words and although there are different opinions about it, e-maintenance is understood as the maintenance based on the use of the Internet for the data and information transmission between system to be maintained and the person in charge of making decisions In the same way, the concept of electronic warranty has been defined as the warranty support that includes management of resources and necessary services that permits proactive decisions in the performance of the technical assistance to the client These applied electronic technologies for example the control or the diagnosis of reclamations under warranty are, in consequence, key factor to reach high levels of quality, reliability, efficiency, and of course customer’s trust.

This chapter discusses the importance of continuous customer relationship management (CRM) in relation to customers' perceptions of service quality Research indicates that measuring quality costs is essential for enhancing both company performance and customer satisfaction Quality assessment can be approached from the user's perspective using marketing standards and statistical analysis of historical data, focusing on the satisfaction of current and potential customers Additionally, manufacturers must adhere to specific rules and guidelines when interacting with consumers, which may vary by market A recent example in Europe is the European norm EN 13269, which provides a comprehensive framework for preparing maintenance contracts, thereby facilitating better service delivery.

This article provides a comprehensive overview of the structure of warranty service contracts, focusing on the essential elements and various aspects related to their content It emphasizes the importance of understanding these contractual documents to ensure clarity and effectiveness in warranty agreements.

In conclusion, this chapter emphasizes the significance of implementing the Six Sigma methodology to enhance after-sales management and streamline decision-making processes Table 14.1 outlines the roles, critical processes, and key activities involved, underscoring the methodology's application in addressing priorities from the warranty program Furthermore, it advocates for a robust cycle of continuous improvement to prevent the recurrence of failures.

Conclusions Extracted from the Different Parts

In continuation, the results achieved during this work that were proposed in Chap 1 are shown here, just as in relation to the different contributions, conferences, magazines, and books:

Various studies, models, and approximations have significantly advanced the identification, analysis, elimination, and prevention of issues arising from failures in industrial assets These research efforts provide valuable insights into failure mechanisms, enabling industries to implement effective predictive maintenance strategies By leveraging data analytics and modeling techniques, organizations can enhance their asset management practices, ultimately reducing downtime and operational costs Furthermore, these methodologies facilitate a proactive approach to risk management, ensuring that potential failures are addressed before they escalate into critical problems.

Recent studies and models have enhanced our understanding of the current state of maintenance and warranty management While it may be overly ambitious to claim that this analysis encompasses all aspects of maintainability and after-sales interactions, the reviewed research allows for the differentiation and selection of strategies to prevent recurring issues through organizational improvements Additionally, contributions from these studies have provided insights into the business realities associated with managing warranty assistance programs, highlighting common challenges that arise in this context.

• 2nd Question: What systems are proposed for after-sales service so that we can the most of the advantages of methodologies that have been successfully applied in other areas?

Leveraging successful technologies from various sectors has enabled us to propose a comprehensive framework presented at conferences [12–17], categorizing techniques into four key phases: effectiveness, efficiency, assessment and control, and continuous improvement This framework is essential for enhancing an organization's maturity in after-sales services Additionally, certain contributions advocate for the adoption of best practices that significantly elevate the quality of management processes.

In Chapter 6, the study focuses on a manufacturer launching products that require warranty services, aiming to address the challenges associated with these warranties The results demonstrate effective methodologies that enhance the warranty process, ensuring improved customer satisfaction and streamlined service operations.

What’s the company’s own perception on its after-sales service?

A maturity matrix is obtained where the level of involvement of each department is quantified

(harvesters and harvester head) that is sold in the first- and second-hand market

Which after-sales service is the most beneficial?

Sales of new harvesters yield significant advantages in after-sales service In contrast, the value of used products often surpasses the objective value outlined in the Analytic Hierarchy Process (AHP) Effective spare parts management is crucial for the customized manufacturing of products at specific stages of production.

From where is preferable to obtain such spare part in that determined moment?

The best place option to get that spare in this context would be from the warehouse, then cannibalization

A water distribution company that suspends the supply due to a network failure

What is the cost of keeping or losing a customer after a failure?

In this context, the intangible costs are estimated at 314.31 €

RAMS (Chap 9) Electromechanical item in the design phase

Which would be the spare part list best recommended for servicing this warranty?

The welding equipment, rotor set, and stator are the three components which reliability decreases

60 % after a year LCC (Chap 9) Faulty engines are repaired providing a repair warranty

How long would that period of time be to carry out the best repair service?

The minimum value is obtained from the NHPP model, considering different percentages of waiting time until the next failure Six Sigma

An automotive company that repeatedly receives the same type of warranty reclamation

How to deal with a reclamation that affects design?

Instruction sheet for defect corrections, obtaining a 70 % improvement (steel was the critical input of the imprinting) Intellectual capital

Water distribution companies that attend similar areas of customers

Which company presents a better investment of its initial budget?

Company B has a larger investment in intellectual capital (best investment of initial budget) Maintainability

Bridge crane that requires technical assistance

How difficult or easy is to technically assist this item?

Graphics are obtained quantifying attributes and variables of maintainability

• 3rd Question: How the after-sales service would be in order to enable us to be more efficient and with a beneficial performance from a business point of view?

The after-sales services play an important role in companies with rising profits.

To effectively enhance customer technical assistance, it is essential to employ tools and methods that adopt a holistic approach, considering all relevant areas such as manufacturing, quality, and finance Both financial and engineering factors must be evaluated, necessitating the translation of technical performance into its economic implications Research presented in various conventions, conferences, and journals has explored the application of Balanced Scorecard (BSC) and Analytic Hierarchy Process (AHP) in warranty program support, as well as the management of risks and costs associated with after-sales service These tools integrate industry methodologies and project management techniques to identify strengths and mitigate weaknesses.

• 4th Question: How would the technical and financial performances in after- sales services be measured in order to make an improvement in management possible?

While the technical and financial impacts have been addressed in question 3, this fourth question wraps up the cyclical process of assessing these impacts and implementing continuous quality improvement techniques Significant contributions to this analysis have been documented in specialized papers published in various journals.

The after-sales service directly impacts technical performance by reducing customer complaints and non-conformities of industrial assets Companies aim for economic profit while fulfilling social and environmental responsibilities, making it crucial to evaluate the economic effects of technical services Monitoring product behavior helps control costs, influencing performance across various departments beyond after-sales Enhancing after-sales service leads to savings that positively affect the entire organization, improving financial outcomes and corporate image Additionally, analyzing product reliability, life cycle costs, customer relationships, and after-sales contracts supports management procedures and facilitates improvements through multidisciplinary teams, such as those using Six Sigma Ultimately, assessing the impact of after-sales service connects technical performance with economic results.

14.2 Conclusions Extracted from the Different Parts 313

• 5th Question: What information must be relevant to make decisions regarding the after-sales service and what are the future researches that arise from this line?

After-sales and maintenance data are often scattered across various databases, making their compilation tedious and time-consuming To address these challenges and provide a comprehensive approach, a procedure has been established to assess the intellectual capital of after-sales service and the maintainability of products This allows for the comparison of relevant data to enhance the performance of technical staff and the organization as a whole Furthermore, managing warranty and after-sales information opens up new avenues for research, such as modeling dynamic systems of products and services and applying Bayesian networks in decision-making scenarios where warranty is a critical variable These topics have been further explored in subsequent conferences.

Future Lines of Research

This research outlines various avenues for further exploration in after-sales services and warranty assistance, emphasizing their holistic impact on businesses, employees, and clients Chapter 2 introduces a generic scenario, suggesting the inclusion of boundary conditions related to product reliability, warranty costs over time, and prioritization of failures when budget margins are negative Chapter 3 discusses potential future research on new economic models for after-sales service management In Chapter 4, a promising direction involves linking warranty management models with production system tools or developing maintenance management models tailored to specific organizations Chapter 5 proposes the application of diverse methodologies and a detailed study of information organization and data requirements for warranty assistance, potentially involving a Six Sigma team Finally, Chapter 6 suggests analyzing various perspectives on best practices in after-sales management of industrial assets.

Understanding the differences in service concepts between emerging and developed countries is crucial for businesses, as these markets have distinct roles—emerging countries often being producers and developed countries serving as consumers This article emphasizes the importance of assessing product life cycle stages—pre-launch, launch, and post-launch—each with unique requirements It aims to provide a foundation for future research in critical analysis, highlighting key aspects necessary for companies to make informed decisions and achieve global objectives Special attention must be given to the corporate environment and the experience of personnel in technical services Future research avenues include logistic support, cost-benefit analysis, and the integration of advanced mathematical methods with electronic technologies to create sophisticated models The role of ICTs in various fields opens up opportunities for exploring concepts like electronic warranties and e-maintenance Furthermore, enhancing after-sales personnel involvement and increasing intellectual capital through training and new techniques are vital for improving warranty assistance effectiveness Lastly, after-sales management presents significant potential for leveraging new technologies and assessing future capabilities in product and service systems, with a focus on using Bayes' network theory to evaluate warranty-related risks.

1 Murthy DNP, Djamaludin I 2002 New product warranty: A literature review Int.

2 Crespo Márquez A, Benoit I 2006 Editorial Special issue on eMaintenance Computers in Industry 57:473-475.

3 International Std 2008 ISO 9001:2008 Sistemas De Gestión De La Calidad AENOR

4 Karim MR, Suzuki K 2005 Analysis of warranty claim data: a literature review, International Journal of Quality & Reliability Management 22(7):667-686.

5 Goodman J 1986 Technical Assistance Research Program (TARP), U.S Office of Consumer Affairs Study on Complaint Handling in America.

6 European Norm 2007 UNE-EN 13269:2007 Mantenimiento Guía para la preparación de contratos de mantenimiento AENOR

7 González-Prida V, Gómez JF, and Crespo Márquez A 2009 Case study: Warranty costs estimation according to a defined lifetime distribution of deliverables 4th World Congress on Engineering Asset Management (WCEAM 2009), Athens, Greece ISBN: 978-1-84996-002-

8 González-Prida V, Crespo Márquez A 2010 Book Review: Reliability Engineering.

Warranty Management and Product Manufacture’’ (By D.N.P Murthy and W.R Blischke).

Production Planning & Control: The Management of Operations, 1366-5871, 21(7):720-721.

9 González-Prida V, Gómez JF, Crespo Márquez A 2010 Estado del arte en modelos de garantía: Una revisión práctica al Marco de la gestión de los costes de garantía Revista Ingenierớa y Gestiún de Mantenimiento Vol Enero/Febrero/Marzo Espaủa 2010.

10 González-Prida V, Gómez JF, López M, Crespo Márquez A, & Moreu P 2010 Warranty cost models State-of-Art: A practical review to the framework of warranty cost management.

Reliability, Risk, and Safety Theory and applications C Guedes Soares et al (Eds), pp 2051-2059 Taylor & Francis Group, London, ISBN 978-0-415-55509-8.

11 Crespo Márquez A, Moreu P, González-Prida V, Gómez J, Parra C 2009 The maintenance management framework: A practical view to maintenance management Taylor & Francis Group, London, ISBN 978-0-415-48513-5, pp 669-674.

12 González-Prida V, Crespo Márquez A 2012 A reference framework for the warranty management in industrial assets Computers in Industry 63:960-971 ISSN: 0166-3615.

13 González-Prida V, Barberá L, Crespo Márquez A, Gómez J 2012 The Management of a Warranty Assistance Program: A suggestion as Reference Framework Advances in Safety, Reliability and Risk Management - Bérenguer, Grall & Guedes Soares (eds) Taylor &

14 González-Prida V, Parra C, Gómez JF, and Crespo Márquez A 2010 Reference framework proposal for the management of a warranty program Euromaintenance 20th International Industrial Maintenance Congress, from the 12th to the 14th of May in the Verona Conference Centre, Italy, pp 100-105.

15 González-Prida V, Barberá L, Gómez JF, Crespo Márquez A 2012 Contractual and quality aspects on warranty: best practices for the warranty management and its maturity assessment.

International Journal of Quality & Reliability Management 29(3), ISSN: 0265-671X, Emerald.

16 González-Prida V, Parra C, Crespo Márquez A, Gómez J 2011 Audit to a specific study scenario according to a reference framework for the improvement of the warranty management ESREL Conference, Troyes (France) Taylor & Francis Group.

17 Costantino F, De Minicis M, González-Prida V, Crespo Márquez A 2012 On the use of Quality Function Deployment (QFD) for the identification of risks associated to warranty programs ESREL Conference, Helsinki (Finland) Taylor & Francis Group.

18 González-Prida V, Gómez JF, Crespo Márquez A 2011 Practical Applications of AHP for the Improvement of Warranty Management Journal of Quality in Maintenance Engineering, 17(2):163-182, Emerald Group Publishing Limited, 1355-2511.

19 González-Prida V, Barberá L, Crespo Márquez A, Viveros P, Kristjanpoller F 2011.

Implementing the Balance Scorecard for the Improvement of the Warranty Management: The Strategic Alignment International Journal of E-Business Development (IJED), 1(1):15-21.

20 González-Prida V, Barberá L, Crespo Márquez A, Arata A, Viveros P, Kristjanpoller F 2011.

Aplicación del Cuadro de Mando Integral para la mejora de la gestión de la garantía: la alineación estratégica Congreso MAPLA 2011, Chile.

21 González-Prida V, Crespo Márquez A, Gómez J 2010 Practical application of an Analytic Hierarchy Process for the improvement of the warranty management The 38th ESREDA seminar and 3rd joint ESREDA/ESRA seminar on Advanced Maintenance Modelling, 4-5th may, 2010, hosted by the regional committee of the Hungarian Academy of Science.

22 Barberá L, González-Prida V, Parra C, Crespo Márquez A 2012 Framework to assess RCM software tools ESREL Conference, Helsinki (Finland) Taylor & Francis Group.

23 González-Prida V, Pérès F, Crespo Márquez A 2011 On the risks and costs methodologies applied for the improvement of the warranty management Journal of Service Science and Management (JSSM) 2(6) ISSN 1940-9907.

24 González-Prida V, Crespo Márquez A, Pérès F, De Minicis M, Tronci M 2012 Logistic support for the improvement of the warranty management Advances in Safety, Reliability and Risk Management – Bérenguer, Grall & Guedes Soares (eds) Taylor & Francis Group, London, ISBN 978-0-415-68379-1.

25 González-Prida V, Kristjanpoller F, Arata A, Crespo Márquez A 2010 Caso de estudio sobre el análisis de la fiabilidad en una planta de triturado de mineral en Chile Revista Ingeniería y Gestiún de Mantenimiento Vol Abril/Mayo/Junio 2010 Espaủa.

26 González-Prida V, Barberá L, Crespo Márquez A 2010 Practical application of a RAMS analysis for the improvement of the warranty management 1st IFAC workshop on Advanced Maintenance Engineering Services and Technology, Lisbon, 1-2 July 2010

27 González-Prida V, Gómez JF, López M, Crespo Márquez A, & Moreu P 2009 Availability and reliability assessment of industrial complex systems: A practical view applied on a bioethanol plant simulation Safety, Reliability and Risk Analysis: Theory, Methods and Applications - Martorell et al (eds), pp 687-695 Taylor & Francis Group, London, ISBN 978-0-415-48513-5.

28 González-Prida V, Barberá L, Crespo Márquez A, Parra C 2012 Warranty period calculation after the repair of a complex industrial asset applying non-homogeneous Poisson Process.

29 González-Prida V, Real C, Barberá L, Crespo Márquez A 2011 Caso de estudio en el sector automovilístico sobre la aplicación de la metodología 6-Sigma en la gestión de la garantía.

Revista Ingenierớa y Gestiún de Mantenimiento Vol Enero/Febrero/Marzo Espaủa 2011.

30 González-Prida V, Barberá L, Crespo Márquez A, 2012 New Services Generated by the e- Technology Applied on the Warranty Management International Journal of E-Business Development (IJED), 2(1):16-22 ISSN: 2226-7336

31 González-Prida V, Barberá L, Crespo Márquez A, Gómez J 2011 ICT application on the warranty management process The ‘‘e-warranty’’ concept ESREL Conference, Troyes (France) Taylor & Francis Group.

32 González-Prida V, Gómez J, Barberá L, Crespo Márquez A 2012 The customer relationship in the warranty management of Distribution Network Service Providers ESREL Conference, Helsinki (Finland) Taylor & Francis Group.

33 Gómez J, González-Prida V, Crespo Márquez A, Parra C 2010 Network maintenance contribution in terms of intellectual capital on distribution network services providers.

Reliability, Risk and Safety - Ale, Papazoglou & Zio (Eds) Taylor & Francis Group, London, ISBN 978-0-415-60427-7.

34 Gómez JF, González-Prida V, López M, Crespo Márquez A 2010 Network maintenance contribution in quality terms on distribution network services providers Reliability, Risk and Safety: Theory and Applications – Briš, Guedes Soares & Martorell (eds) Taylor & Francis Group, London, ISBN 978-0-415-55509-8

35 Moreu P, González-Prida V, Barberá L, Crespo Márquez A 2012 A practical method for the maintainability assessment using maintenance indicators and specific attributes Reliability Engineering and System Safety 100:84-92 ISSN: 0951-8320.

36 González-Prida V, Moreu P, Crespo Márquez A, Barberá L 2011 Norma de mantenibilidad:

Propuesta para la evaluación de la mantenibilidad en activos industrials Ingeniería y Gestión del Mantenimiento, N 74, Jul/Ago/Sept 2011, pp 24-37.

Tiêu đề	After-sales Service of Engineering Industrial Assets
Tác giả	Vicente González-Prida Díaz, Adolfo Crespo Márquez
Trường học	Universidad de Sevilla
Chuyên ngành	Industrial Management
Thể loại	ebook
Năm xuất bản	2014
Thành phố	Sevilla

Định dạng
Số trang	328
Dung lượng	8,59 MB