Ebook advanced design and manufacture to gain a competitive edge

Advanced Design and Manufacture to Gain a Competitive Edge Xiu-Tian Yan • Chengyu Jiang • Benoit Eynard Editors Advanced Design and Manufacture to Gain a Competitive Edge New Manufacturing Techniques and their Role in Improving Enterprise Performance 123 Xiu-Tian Yan, BEng, PhD, CEng, MIET, FITL Department of Design, Manufacture and Engineering Management (DMEM) University of Strathclyde James Weir Building 75 Montrose Street Glasgow G1 1XJ UK Benoit Eynard, PhD, MAFM, MDS Department of Mechanical Systems Engineering University of Technology Compiègne BP60319 60203 Compiègne Cedex France Chengyu Jiang, PhD Northwestern Polytechnical University 127 Youyi Xilu Xi’an 710072 Shaanxi China ISBN 978-1-84800-240-1 e-ISBN 978-1-84800-241-8 DOI 10.1007/978-1-84800-241-8 British Library Cataloguing in Publication Data Advanced design and manufacture to gain a competitive edge Engineering design - Congresses Manufacturing processes - Congresses I Yan, Xiu-Tian II Jiang, Chengyu III Eynard, Benoit 620'.0042 ISBN-13: 9781848002401 Library of Congress Control Number: 2008928772 © 2008 Springer-Verlag London Limited Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency Enquiries concerning reproduction outside those terms should be sent to the publishers The use of registered names, trademarks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made Cover design: eStudio Calamar S.L., Girona, Spain Printed on acid-free paper springer.com Preface Manufacturing industry has been one of the key drivers for recent rapid global economic development Globalisation of manufacturing industries due to distributed design and labour advantage leads to a drive and thirst for technological advancements and expertise in the fields of advanced design and manufacturing This development results in many economical benefits to and improvement of quality of life for many people all over the world This rapid development also creates many opportunities and challenges for both industrialists and academics, as the design requirements and constraints have completely changed in this global design and manufacture environment Consequently the way to design, manufacture and realise products have changed as well More and more design and manufacture tasks can now be undertaken within computer environment using simulation and virtual reality technologies These technological advancements hence support more advanced product development and manufacturing operations in such a global design and manufacturing environment In this global context and scenario, both industry and the academia have an urgent need to equip themselves with the latest knowledge, technology and methods developed for engineering design and manufacture To address this shift in engineering design and manufacture, supported by the European Commission under the Asia Link Programme with a project title FASTAHEAD (A Framework Approach to Strengthening Asian Higher Education in Advanced Design and Manufacture), three key project partners, namely the University of Strathclyde of the United Kingdom, Northwestern Polytechncial University of China, and the Troyes University of Technology of France organised a third international conference This conference aims to provide a forum for leading researchers, industrialists and other relevant stakeholders to exchange and debate their research results as well as research issue This conference focuses on papers describing the cutting edge research topics, fundamental research issues related to the global advanced design and manufacture and recent industrial application papers with a goal towards bringing together design and manufacture practitioners from academics, government organisations, and industry from all over the world The conference aims to cover the recent advancement and trends in the area of design and manufacturing and to facilitate knowledge sharing, presentations, interactions, discussions on emerging trends and new challenges in design and manufacturing fields The particular focus of this conference is on the understanding of the impact of distributed team based design and manufacture on vi Preface research and industrial practices for global companies Being the third conference in this theme since 2004, the aims of the conference are: (a) to become a regular major forum for the international scientific exchange on multi-disciplinary and inter-organisational aspects of advanced engineering design and manufacturing engineering; and (b) to provide opportunities in presenting and formalising the methods and means for industrial companies to design and manufacture successful products in a globally distributed team based environment It is well know that engineering design activities are mostly undertaken in the developed countries, represented by European, American and Japanese companies, whereas more manufacturing actives are undertaken by more companies that are located in Asian This trend may start to change as some engineering design work is gradually outsourced in Asia companies as well This increasing geographical distribution of tasks involved in the whole product realisation process brings great challenge as well as huge benefits for all stakeholders It is therefore timely to organise this international conference and bring together leading researchers, academics and industrialists to discuss these issues and promote the future research in these important areas Out of 385 full papers submitted, the organisers use the review results from international reviewers, and finally selected 174 papers for publication Based on the topics of the paper submitted, editors have divided them into relevant chapters and produced two books This book focuses on the advancements in simulation and virtual reality in engineering design and manufacture, advancement in various manufacturing aspects, including manufacturing tool design, process planning, special manufacturing techniques, MEMS and industrial applications of design and manufacture techniques and practices The book hence contains a selection of refereed papers presented at the conference It represents the latest thinking on manufacture from mainly Europe and Asia perspectives It includes 88 papers from 174 accepted refereed papers, focusing on the advancement in the area of manufacturing technologies, supporting tools and special techniques More specifically, the book covers the following eight broad topics in manufacturing and associated tools and each of these has been called a chapter: Chapter 1: Simulation and Virtual Reality Enabled Design and Manufacture Analysis Simulation and virtual reality have been developed over recent years to provide effective and rapid evolution of design solution for both products and manufacturing systems This chapter collects sixteen papers relating to the use of these technologies and provide a collection of latest technological development and their applications mainly in manufacturing operations, such as assembly, robotics and so forth Chapter 2: Materials Design and Processing Material design and processing remain to be a critical discipline for product realisation Recent development in the field shows an increasing trend to integrate material design with manufacturing and product developments This can bring the benefits of designing and manufacturing complex components using these Preface vii developments from early material design stage This chapter collects seven papers on material and their property related research Chapter 3: Manufacturing System Design and Analysis This chapter contains eighteen papers on various types of manufacturing machine design and development Examples include deigns of multi-axis machine tool, reconfigurable production line design, ball screw feed system and as extensive as wireless temperature measurement system design Modelling, testing and evaluation techniques have been used by authors to validate their design solution in the process Chapter 4: Machine Tools and Manufacturing Technologies Machine tools have been and will still be the key tools used in manufacturing industry and it is inevitable that there are a large group of researchers are working in the field to have better understanding of various aspects of the operations of machine tools and associated manufacturing techniques Seventeen papers have been selected in this chapter to reflect the latest research understanding and findings in the field Topics included in the chapter covers the tooling life analysis, machine parameter optimisation, joining process between steel and aluminium, and high speed machining and so forth Chapter 5: Manufacturing Planning Manufacturing operation planning is still a key to the lean manufacture and responsive manufacturing operations Well planned operations will reduce product manufacturing time and improve product quality This chapter includes eleven papers on the process routing planning, service driven information processing for planning and simulation, robotic hand grasp planning, engineering of economy of scope system design and plan etc Chapter 6: MEMS MEMS has been a popular research area in recent years and there have been significant development in the field, resulting in more environmentally friendly manufacturing technologies as these micro-machine tools consume significantly less energy and space to manufacture miniature sized components and products Eight papers have been chosen to illustrate a range of topics including micro-hole drilling, punching, machining, micro-assembly maybe using desk-top microfactory, and design issues related to laser based micro-manufacturing Chapter 7: Special Manufacturing Techniques and Industrial Applications The final chapter of the book illustrates the latest development on some special manufacturing techniques, including Electrical Discharge Machining (EDM) techniques, combined continuous grinding and electrochemical processing techniques, air-bulging techniques used in in-mould decoration design and thermoforming This chapter also has emphasis on the industrial applications of these new or improved special manufacture techniques Several industrial application s have been shown in the chapter viii Preface It is the editors’ believe that by introducing these advanced design and manufacturing techniques developed recently in the manufacturing operations, that many enterprise will be able to gain competitive advantage The editors of the book: Xiu-Tian Yan, Chengyu Jiang and Benoit Eynard Acknowledgements The editors would like to express their sincere thanks to the Advisory Scientific Board for their guidance and help in reviewing papers Editors also would like to express their gratitude to the extended reviewers and the conference Secretariats Dr Fayyaz Rehman, Professor Geng Liu, Professor Jingting Yuan, Professor Hong Tang and Mrs Youhua Li for their patience and huge effort in organising the paper review process and answering numerous queries from authors Without their support, it would have been very difficult to compile this book The Editors would also like to thank Dr Andrew Lynn for his kind support and maintenance of the conference paper management system which he developed for journal editing purpose With a magic touch and modification, this system has provided with editors a wonderful tool to manage over eight hundred submissions in total The Editors would also like to thank Mr Frank Gaddis for his help and design of the book cover The editors of the book would also like to thank the sponsoring organisations for their support to the organisation of the Conference The Organisers of the ICADAM 2008 Conference: x x x The University of Strathclyde Northwestern Polytechnical University The University of Technology Troyes The Conference Sponsors: x x x x European Commission; National Natural Science Foundation of China; Institution of Engineering Designers, UK; Institution of Mechanical Engineers, UK; x Acknowledgements x x x x The Design Society – A Worldwide Community; The Chinese Mechanical Engineering Society; Shaanxi Mechanical Design Society; Northwestern Polytechnic University – 111 project ICADAM2008 Organising Committee Conference Co-Chairmen: Professor Chengyu Jiang, President of Northwestern Polytechnical University, Xian, China Professor Neal Juster, Pro-Vice Principal of the University of Strathclyde, UK Dr Xiu-Tian Yan, The University of Strathclyde, UK Advisory Scientific Board Chair: Mr William J Ion, the University of Strathclyde, UK Dr Muhammad Abid, Ghulam Ishaq Khan Institute of Sciences and Technology, Pakistan Professor Xing Ai, Academician of CAE, Shandong University, China Professor Abdelaziz Bouras, University of Lyon (Lyon II), France Dr Michel Bigand, Ecole Centrale de Lille, France Dr Jonathan Borg, University of Malta, Malta Professor David Bradley, University of Abertay, UK Prof David Brown, Editor of AIEDAM, Worcester Polytechnic Institute, USA Professor Yang Cao, Hainan University, China Professor Keith Case, Loughborough University of Technology, UK Professor Laifei Cheng, Northwestern Polytechnical University, China Professor P John Clarkson, University of Cambridge, UK Professor Alex Duffy, University of Strathclyde, UK Dr Shun Diao, China National Petroleum Corporation, China Professor Benoit Eynard, Troyes University of Technology, France Professor K Fujita, University of Osaka, Japan Professor James Gao, Greenwich University, UK Professor John S Gero, University of Sydney, Australia Professor Philippe Girard, University of Bordeaux 1, France Professor Dongming Guo, Dalian University of Technology, China Professor Lars Hein, Technical University of Denmark, Denmark Professor Bernard Hon, University of Liverpool, UK Professor Imre Horvath, Delft University of Technology, Netherlands Professor Weidong Huang, Northwestern Polytechnical University, China Professor Sadrul Islam, Islamic University of Technology, Bangladesh Model Driven Engineering of Economy of Scope Systems Z Cui, R.H Weston MSI Research Institute, Loughborough University, UK Abstract As product lifetimes fall so must the useful life of production systems, unless the next generation of production systems can realise economies of scope, i.e be capable of efficient reconfiguration to realise multiple value streams through their lifetime Analysis is made with reference to product dynamics observed in the furniture industry Three common business models for this industry are explicitly documented using an ISO Enterprise Modelling technique This gave rise to specific case Enterprise Models (EMs) that provide input data and structural design guides to ‘context dependent Simulation Models (SMs)’ The SMs can be reused on an ongoing basis to inform ‘process’, ‘resource’ and ‘product’ aspects of production systems design The SMs can also predict business benefits arising from alternative configurations of production systems The modelling methods and concepts have been applied to case study production systems drawn from the furniture industry and have enable possible future impacts of product variance and product volume variation to be analysed Keywords: Flexible Manufacturing Systems, Enterprise Modelling, Simulation Modelling, Economy of Scope and Scale Introduction The present literature on production systems introduces notions about economies of scale and scope (1) It has also qualitatively linked these notions to related ideas about: ‘extending the useful lifetime of production systems’ (2,3); ‘designing lean and agile production systems’ (4); and ‘mass customisation, product modularisation and postponement (5,6) But there remains a lack of quantifiable knowledge about the nature and impact of such linkages on the performance of multi-product realising systems This paper describes a new integrated modelling approach which can be use to create re-useable models of production systems and to subject these systems in a virtual environment to impacts arising from product dynamics The integrated approach gains synergistic benefits from using Enterprise Modelling (EM) concepts, to capture the ‘business context’ in which the production system to be designed or changed must operate, and a Simulation Modelling (SM) tool, to computer execute and quantify operational behaviours and performances of 698 Z Cui and R.H Weston alternatively design production systems SMs of production systems are built as comprising three interdependent sub-systems concerned with ‘process’, ‘resource’ and ‘product/work flow’ perspectives This allows alternative configurations of production system to be configured and represented by SMs; so that experiments can be designed to study impacts of changes in any of these sub-systems on overall behaviours and performance Of particular concern in this paper are impacts arising from product dynamics Economy of Scope Definitions Figure was constructed by the authors to characterise what they mean by the term economy of scope production system The figure shows three cases of production system configuration Case is not considered to realise economies of scope, because it can only deal with one product ‘type’ within a ‘class’ The terms ‘type and ‘class’ are defined by Figure It follows that if significant production volume variation occurs in a single product Case system then the economy of that system may come into question However if the volumes are sufficiently high then economies of scale can be realised by Case systems Case systems can realise both economies of scope and scale because they can realise more than one value stream associated with a number of product types within a class (or product family) The notion of economy of scope comes from the fact that if production volumes fall for one product type within its scope it may be Figure Possible alternative configurations of multi-product realisation systems and related ‘flexibility’ assumptions to be tested Model Driven Engineering of Economy of Scope Systems 699 possible to compensate by an increased volume requirement for another within the systems’ scope Naturally for this reason Case production systems have the greatest scope and therefore have the greatest potential (in theory) to realise economies of scope Figure Assumptions about causal links between product and process change to be tested Figure illustrates posible impacts on production systems design arrising from product varience, which is defined in this study as variations between products belonging to a ‘type’ or ‘class’ Section 3.0 gives some examples of product varience Figure also gives examples of the kinds of ‘change competency’ needed to realise economies of scope However the following question remains a major concern to industry: How can manufacturers systematically design and engineer change through the lifetime of economy of scope production systems? Such that they continue to perfomed competitvely despite many changing factors that impact on them; and so so that needed re-configurations can be achieved rapidly and effectively, protecting investments and mitigating business risks The research of the present authors has investigated an integrated use of ‘state of the art modelling technologies’ with the purpose of informing decision making about production systems design By so doing their modeling approach offers a systematic and quantitative way of answering the question raised in the forgoing The approach is under ongoing development and is designed in this paper with reference to case study examples 700 Z Cui and R.H Weston Choice of Study Domain and Related Product Variance The furniture industry was chosen as a subject of study, for which three prime business models are in use namely ‘Fixed furniture’ production; ‘Flat Pack furniture’ assembly and ‘Custom furniture’ fitting Choice of study domain was partly because of its product dynamic; which is manifest in (i) significant variation between product designs (termed product varients in this study), (ii) significant variation in production volume requirements in a given time frame, (iii) frequent variation in the mix of products needed in a given time frame and (iv) the introduction of new product variants year on year It follows that furniture production systems realize products used for a variety of purposes and in various quantities, sizes, shapes, finishes, and so forth Figure was constructed to illustrate some of the purposes, common features and common products produced by this industry and indicates the predominant business models use to realise them Area of Home Common Features * standard ‘spaces’ Applicable Business Models * cabinets * tables * chairs * work tops * flat pack (main) * fixed (main) * wardrobes * dressing tables * beds * chairs * flat pack (minor) * fixed (main) * custom (main) * cabinets * tables * chairs * flat pack (minor) * fixed (main) * standard ‘people ergonomics’ * occasional tables * sofas * chairs * flat pack minor) * fixed (main) * mainly aesthetics then functionality * book cases * non-standard ‘spaces’ * computer desks * tables * chairs * shelving (can standardise most furniture dimensions) kitchen Common Products * standard ‘people ergonomics’ (can standardise many furniture features) * functionality then aesthetics (in most kitchen furniture) * custom (minor) value * reliability & safety key * non-standard ‘spaces’ bedroom (exceptionally can standardise dimensions) * standard ‘people ergonomics’ * BOTH aesthetics & functionality * non-standard ‘spaces’ (exceptionally can standardise dimensions) dining room * standard ‘people ergonomics’ * mainly aesthetics then functionality * non-standard ‘spaces’ (exceptionally can standardise dimensions) lounge office (at home) (exceptionally can standardise dimensions) * standard ‘people ergonomics’ * functionality & ergonomics aesthetics & customisation * custom (minor) * custom (minor) * flat pack (fairly minor) * fixed (main) * custom (minor) important Figure ‘drivers’ for product variance (2) Integrated Enterprise and Simulation Modeling in Fixed Furniture Assembly Operations Figure shows an example activity diagram created to represent current practise in a Case Study Company making Fixed Furniture This diagram explicit document how business process (BPs) and Enterprise Activities (EAs) lead to furniture production in conformance with BP71 The assembly section is concerned with realising part of business process BP71-2, namely ‘Assemble Carcasses & Fit Components’ Modelling studies described in this paper are focused on the Model Driven Engineering of Economy of Scope Systems 701 assembly of Farm House Table and Drop Leaf table Table products which are two of 350 product types produced by the Case Study Company Figure Activity Diagram of Case Study Company Detailed study of the sequence of operations used to assemble Farm House tables showed that business process BP71-2 can be decomposed into EAs, which are illustrated in Figure Each of these EAs were studied in detail to develop groundwork knowledge needed to create SM1; Here detailed studied centred on processing activities and routes, and on needed human and other resources to realise each EA, and on possible grouping into ‘roles’ that can be assigned to Work Centres (WCs) incorporated into SM1, In the case of SM1, the enterprise activities of EA 7.1.2.1 is executed by WC1 Collect component; then EA 7.1.2.2 is executed by WC2; EA 7.1.2.3 is executed by WC3; and finally EA7.1.2.4 is executed by WC4 Following the same method, the assembly process of a second type of table (namely Drop Leaf tables) was modelled based on the capture of specific company information; the aim here was to use the same modeling approach to create SM2; which is showed in figure Both SM1 and SM2 are economy of scale systems as defined in section 2.0 702 Z Cui and R.H Weston Figure Farm House table assembly processes simulation model Figure Drop Leaf table assembly processes simulation model Model Driven Engineering of Economy of Scope Systems 703 Create Multi-product Model SM3 and Compare with Single-product Models The next production system studied was a possible future configuration able to realise dual economies of scope and scale Farm House and Drop Leaf tables are fed into SM3 such that they share one assembly process with the same set of work centers and their underlying human and technical resources The screen shot of SM3 is shown in figure When comparing the simulation results of the modelled single and multiproduct assembly systems, it was decided that there are three main performance measures that should be taken into account, bearing in mind the general aims and objectives of the authors, namely: 1) Lead time spending in each model; 2) Utilization of machines and human resources; 3) Revenue and Cost comparisons These factors were calculated for different simulation runs and example results are compared graphically in Figures 8, and 10 From figure 8, we can see that the average time in the system of each work item for both Farm House and Drop Leaf table in the multi-process model SM3 is much higher than for the single product models in SM1 and SM2 This was expected because in SM3, FH and DL table work items have to share the available time of machines and human resources used to realise processing operations, for example in WC5 Bench1, they share the vertical sander to get both types of leg sanded For operation times which are distinct then simulated flows of work items are differentiated via numeric labels assigned to work items at work entry points of SMs SM3 Figure Economy of Scope configuration of multi-product model 704 Z Cui and R.H Weston         WLPHLQV\VWHP   )+PRGHO '/PRGHO 0XOWL)+ 0XOWL'/ Figure Comparison of lead time between economy of scale and scope models Figure compares the utilization of Bench1 (one of the WCs) which has competencies assigned to carry out the operations needed to assemble under frames and fit under frame to tops    %HQFK  +XPDQUHVRXUFH    )+PRGHO '/PRGHO 0XOWLPRGHO Figure Comparison of unitization between economy of scale and scope models This illustration shows that in the multi-product model SM3, the utilization of both bench and human resources (associated to WC Bench1) will be higher than that in either SM1 or SM2 Revenue generation and Cost consumption comparison between multi and single product models is illustrated in figure 10 These two figures show that economy of scope systems can perform more cost effectively With more product types the effectiveness will increase   5HYHQXH  &RVW   )+PRGHO '/PRGHO PXOWLPRGHO Figure 10 Comparison of profit between economy of scale and scope models Model Driven Engineering of Economy of Scope Systems 705 Reflections and Conclusions Figure 11 summarise the simulation modeling studies reported in this paper, where SM1 and SM2 are economy of scale systems SM3 has dual economy of scope and scale systems Current modeling studies are concrened with achieving increased economy of scope as illustrated by SM4 SM1: only economies of scale possible SM2: only economies of scale possible FH Table ‘as is’ process multiple but dynamic instances of FH Table pushed into the system DL Table ‘as is’ process multiple but dynamic instances of DL Table pushed into the system P Wi P Wo Wi Wo R R FH Table ‘as is’ (human & machine) resource systems DL Table ‘as is’ (human & machine) resource systems SM4: greatest economies of scope & scale shown SM3: possible dual economies of scope & scale multiple but dynamic instances of Table Top components FH Table + DL Table combined ‘as is’ process multiple but dynamic instances of FH Table pushed into the system W i (A) W i(TT) P Wo W i (A) multiple but dynamic instances of FH Table pushed into the system R FH Table+ DL Table shared resource systems P multiple but dynamic instances of Table Under Combined ‘as Frame components W i (UF) is’ Table Frame P’s R (shared for all Tops) multiple but dynamic instances of Table Leg components W i(TL) FH Table + DL Table combined final assembly ‘as is’ process P Combined ‘as is’ Table Top P’s R (shared for all Tops) P i R Wo P Combined ‘as is’ Table Leg P’s R (shared for all Tops) FH Table+ DL Table Final Assembly shared resource system Figure 11 economy of scale and scope models summary The project has case study tested a novel way of systematically designing and quantitatively predicting performances of economy of scope systems When so doing it had contributed new understandings about: How different types of ‘model’ can usefully characterize the ‘business context’ of economy of scope systems Characterization is made in respect to: ‘product variance’ in that industry; creating text descriptions of different business models used by that industry; and by using an ISO EM technique to explicitly model the network of business processes used by the industry concerned It appears that this model has many possible applications which the present authors have not yet have time to explore; including the provision of a basis for reasoning about ‘possible impacts of ‘product dynamics of the various industry ‘actors’ participating in a given product realizing chain How specific cases of EM can be use to structure and inform the creation of ‘context dependent simulation models’ The subsequent computer 706 Z Cui and R.H Weston execution of these SMs has generated alternative behaviors of both single product and multiple product realizing assembly systems This has allowed performance criterion of alternatively configured economy of scope and scale production systems to be compared How generic reference models of economy of scope and scale production systems, can help guide the design and testing of ‘economy of scope production systems’ The use of new understandings generated by this project might ultimately guide industry in regard to: investment planning in existing and new production systems; planning of new product introductions, e.g into existing or new production systems; and planning and scheduling of existing production systems subjected to on-going product dynamics References [1] Vernadat.F.B (1996), Enterprise Modeling and Integration: Principles and Applications Chapman & Hall, 2-6 Boundary Row: London, UK [2] Yasuhiro Monden (1998), Toyota Production System, An Integrated Approach to JustIn-Time, Third edition, Norcross, GA: Engineering & Management Press [3] Levinson, William A (2002), Henry Ford's Lean Vision: Enduring Principles from the First Ford Motor Plant, Productivity Press Hirano, Hiroyuki and Makota, Furuya (2006), JIT Is Flow: Practice and Principles of Lean Manufacturing, PCS Press, Inc [4] Loe, N.(1998), Postponement for mass Customisation, Chapter 5, in Gattorn J ; Strategic Supply Chain Alignment, Gower [5] Mason-Jones R, Naylor J B, Towill D R (2000), Engineering the Leagile Supply chain- International Journal of Agile Manufacturing System Vol 2, No.1, pp54-61 [6] Ian, Christian Et al Agile Manufacturing Transitional Strategies, Manufacturing Information Systems: Proceedings of the Fourth SME International Conference [7] AMICE (1993) CIMOSA: Open System Architecture for CIM, 2nd extended and revised version, Springer-Verlag, Berlin [8] Weston R.H., Zhen M, Ajaefobi J.O., Rahimifard A., Guerrero A., Masood T., Wahid B., Ding C.,(2007), Simulating Dynamic Behaviours in Manufacturing Organizations, Int Conf on Industrial Engineering and Systems Management, IESM [9] Rahimifard, A and Weston, R H (2006) The Enhanced Use of EM Based techniques to Support Factory Changeability, to IJCIM 17.12.04 revision 3.3.06, accepted 6.4.06 proofs IJCIM Customer Requirement Translation and Product Configuration Based on Modular Product Family Guangxing Wei, Yanhong Qin Management School, Chongqing Jiaotong University, Chongqing, 400074, China Abstract Firstly, this paper establishes the modular structure of product family and then decomposes it into generic modules Secondly, the module model represented by attribute variable is formated for each generic module According to quality function deployment, the mapping of customer requirements to module attributes is constructed, which can determinate the attribute value and weight of module model Thirdly, by searching the candidate set of modules which best satisfy customer requirements, the candidate modules are combined efficiently subjecting to some constraints in the structure of modular product family from down to top Keywords: Generic Module, Modular Product Family, Product Configuration Introduction In an age when consumers demand high-quality, low-priced and customized products, the competition among firms has been aiming at product variety and speed to market Mass customization aiming at delivering an increasing product variety that best serves customer requirements while keeping mass production efficiency, has recently received numerous attention and popularity in industry and academia alike [1] A methodology of product family architecture (PFA) was developed to rationalize product development for mass customization and the diverse customers requirements are matched through systematic planning of modularity in functional, technical and physical views Furthermore, mapping of functional requirements to specific modules is considered [2] The product variety optimization is demanded to determine the attributes of modules and their combination under fixed product architecture Fujita [3] proposed an optimization method of module combination for products in a family Some authors used the unified modelling language (UML) to describe a product family, and the method also focuses on how the customers’ functional requirements can be translated into a selection of specific modules in the product family Jørgensen [4] established modular structure of product family, and illustrated the constraints relevant to module type and attribute of different module types or in the same module type A module type is a model of the set of modules, which are interchangeable, perhaps with some restrictions But he didn’t solve the problem how to choose the exact 708 G.Wei and Y Qin modules for the specific customer requirements Fujita [3] and Wang [11] have developed an optimization method based on simulated annealing technique for the assemble-to-order (ATO) manufacture paradigm But they didn’t formulate how to match modules efficiently when there were a large number of various modules in the module case base To solve the above problems, this paper is organized as follows Based on functionality analysis of each product in the same product family, section decomposes the product family into various generic modules from top to down, and then the module model for each generic module is established and denoted by attribute variables In section 3, by reference to quality function deployment, the mapping of customer requirements to technique requirements and continuously, that of technique requirements to module attribute requirements are formed, which can determinate the value and weight of each module attribute variable Section searches the candidate set of modules, which best satisfy customer requirements on the certain module model accordingly, and then the candidate modules are combined efficiently under the relevant constraints 2.1 Modular Product Family Module Model and Generic Module Based on analyzing products that share common functionality but different performances or different specifications, design for modular product decomposes the products into functional modules, and thereby various products can be configured by choosing and combining the various functional modules to satisfy the various customer requirements The concepts of modules and modularity are essential to product family architecture and design for mass customization While a module is a physical or conceptual grouping of components that share some characteristics, modular technology tries to separate a system into independent modules that can be treated as logic units [5] On the design principle of product family and modularity, the product family can be decomposed into a series of generic module (GM), based on analyzing the functionality of various products in the same product family Figure illustrates the product family represented as the root node of the tree Decomposing the product family into various GMs , the root node has some child nodes denoted as GM a , GM b and GM c , in which some GMs can be decomposed into the lower hierarchical generic modules The number of hierarchy should be reasonable, because too meticulous granular of GMs will cause complexity of management and combination of modules But if the granular is too rough, it will be unfavourable to match the modules with the customer requirements exactly In this way, the set of GMs , which is {GM a , GM b , GM c } or {GM a , GM d , GM e , GM c } , can denote the product family Each module case belonging to same generic module has similar attributes, similar structure, and the same interface but different attribute value To keep consistence, the common module in the product family can also be regarded as a generic module, but it involves only one module case, e.g the GM a The Customer Requirement Translation and Product Configuration 709 functionality analysis is the basic principle to realize modular product family Different modules in the same generic module should have unattached functionality, therefore there is more agility, adaptability and no redundancy functionality while combining the modules PF GMa GMd GMb GMc GMe Figure The tree of generic module in product family For each generic module, a module model can be established, and each module model can be regarded as a configurable unit Modules derived from the same module model belong to the same generic module The module model can be described by multi-attributes [6], when some attributes can be evaluated by many values available, the attribute can be treated as variable, i.e attribute variable in module model, called module attribute variable Different values of partial or all module attribute variable may lead to different modules in the same generic module 2.2 Module Attribute Variable For a specific modular product, value of each module attribute variable is certain But the value of all module attribute variables of product family is uncertain, only a domain corresponding to each attribute variable For some GMs , they involve only one module, e.g GM a , so the value of module attribute variable is certain To keep consistence, however, we denote the corresponding module model with the module attribute variables, e.g Ma is denoted by Aa1 and Aa2, but there is only one element in the domain of each attribute variable All attribute variables can express the product family For example, we can denote the product family in the figure as A( MPF ) { Aa1 , Aa , Ad1 , Ae1 , Ae2 , Ac1 , Ac , Ac3 } When each attribute variable in the above A(MPF ) is assigned with a value which subjects to the related constraints, a specific product can be decided and configured And when each attribute variable of certain module model is assigned with a value subject to the related constraints, a specific module can be determinated Definition of the attribute variable should be simplified under the precondition of design, manufacture and assemble constraints The domain of the attribute variable should be fixed according to customer requirement of the attribute variable and design specification of product structure Sometimes, for the complex structure and functionality of product or module, we can set detail attributes for the module model in order to search the special module case matching customer requirements better According to the domain form of module attribute variable, the attribute variable can be divided into 710 G.Wei and Y Qin continuous variable and discrete variable Let M denote a module model and hereby {M , M ," , M m } denote the product family, in which M i is a random module model and the related set of attribute variable is A( M i ) { A j ( M i ) j 1,2,", ni } , where ni denotes the number of attribute variable in M i Analogously, the set of attribute variable that is denoted as A( MPF ) { A j ( M i ) i 1,2,"m; j 1,2,", ni } can represent the product family as long as they don’t depend on each other Let a j (M i ) represents the value of the j th variable A j ( M i ) MPF Ma Aa1 Mb Aa2 Md Ad1 Mc Me Ae1 Ac1 Ac2 Ac3 Ae2 Figure The tree of module model of modular product family Customer Requirement Translation Customer requirements involves those of functionality, performance, appearance, price and dimension, etc When customer input requirements in online shopping malls and comparison sites on the Internet, by referring to classified customer cluster, the requirements will be classified into similar customer cluster in order to search certain product family that can satisfy the customer requirements [10] As a matter of fact, the individual customer requirements can be translated into the value of each attribute variable in all module models in a certain family The customer requirements should be understood exactly and be inducted appropriately After the customer requirements are translated into technique requirements, i.e the information about general technique character, the certain technique requirements should be translated into value information about the attribute value of each module model Here, the product in need is called target product and analogously, the module that can be combined with other modules to satisfy customer requirements are called target module Quality function deployment (QFD) is an important method to analyze customer requirements [7] By product planning matrix customer requirements are mapped to technique requirements and the module deployment matrix is proposed to translate the technique requirements to value and weight of each module attribute variable Customer Requirement Translation and Product Configuration 711 Table Product Planning Matrix Customer requirements Weight Character Matrix Target value of technique requirement Important degree of technique requirement Item of technique requirement In Table 1, the first row implies customer requirements listed out And crwi (i 1,2,", p ) denotes weight of the i th customer requirement for deciding to buy the product, then the related vector is represented by (crw1 , crw2 ,", crw p ) with the restriction T >@ 6crwi ª t11 t12 " t1q º » « «t21 t 22 " t 2q » « # # # » » « ¬«t p1 t p " t pq »¼ and In this way, a matrix of product planning includes B ª b11 b12 " b1q º » « «b21 b22 " b2q » , « # # # » » « b b b " pq »¼ ¬« p1 p in which is the total number of p items of customer requirements, q is the total number of general technique characters in the target product In matrix T, t ij denotes the value of the j th technique character that can satisfy the i th customer requirement The experts can analyze customer requirement according to quality function deployment and gradually come to the matrix T In matrix B, bij implies the correlative degree of i th customer requirement and the j th general technique character Let denotes “highly correlated”, denotes “correlated” and 1denotes “lowly correlated” If there is no correlation between the i th requirement and the j th technique character, then bij The customer requirements can be translated into technique requirements in product planning matrix Matrix T indicates that individual customer requirements may cause different values for some general technique characters Thus, a general technique character may correspond to a range but not a certain value But in order to get a certain value for each technique character, we adopt the weighted average to deal with the range, and then the certain value replaces the range In this way, let t *j denote the target value (i.e weighted average p value) of the j th technique requirement Then, t *j ¦ crw u t i ij Furthermore, the i p related vector is (t1* , t 2* , " , t q* ) Besides, let tw j ¦ crw u b i ij denote the important i degree of the Here, both j th technique character, then the related vector is (t1* , t 2* , ", t q* ) and (tw1 , tw2 ,", twq ) will be used in Table to compute the value and weight of module attribute variable In the modular product family, a random module model A( M i ) { A1 ( M i ), A2 ( M i ),", Ani ( M i )} (tw1 , tw2 ,", twq ) Mi is represented by Similar to product planning matrix, module deployment matrix includes the correlative matrix of technique requirements and [...]... to a LQG Controller Design 137 S.G Khan, W Naeem, R Sutton and S Sharma GA-based Automatic Test Data Generation for UML State Diagrams with Parallel Paths 147 C Doungsa-ard, K Dahal, A Hossain, T Suwannasart Chapter 2 Materials Design and Processing 157 Rational Synthesis of Calcium Phosphates with Variable Ca/P Ratios Based on Thermodynamic Calculations 159 Qingfeng Zeng, Jiayin... Computing Techniques to a LQG Controller Design 137 S.G Khan, W Naeem, R Sutton and S Sharma GA-based Automatic Test Data Generation for UML State Diagrams with Parallel Paths 147 C Doungsa-ard, K Dahal, A Hossain, T Suwannasart Simulation-Enabled Approach for Defect Prediction and Avoidance in Forming Product Development M.W Fu and J Lu Department of Mechanical Engineering, The Hong Kong Polytechnic... Gaskets Under Combined Internal Pressure and Thermal Loading 855 Muhammad Abid, K .A Khan, J .A Chattha Experimental Research and FEM Analysis of the Two-Axle Rotary Shaping with Elastic Medium 865 Shihong Lu, Xia Jin, Juan Bu Application of Artificial Muscles as Actuators in Engineering Design 875 Zhun Fan, Kristoffer Raun, Lars Hein, Hans-Erik Kiil Author Index 885 Chapter 1 Simulation... Simulation and Virtual Reality Enabled Design and Manufacture Analysis Simulation-Enabled Approach for Defect Prediction and Avoidance in Forming Product Development 3 M.W Fu and J Lu A Case Study to Support Conceptual Design Decision Making Using Context Knowledge 13 Fayyaz Rehman, Xiu-Tian Yan Dynamic and Visual Assembly Instruction for Configurable Products Using Augmented Reality... University of Strathclyde, UK Contents Chapter 1 Simulation and Virtual Reality Enabled Design and Manufacture Analysis 1 Simulation-Enabled Approach for Defect Prediction and Avoidance in Forming Product Development 3 M.W Fu and J Lu A Case Study to Support Conceptual Design Decision Making Using Context Knowledge 13 Fayyaz Rehman, Xiu-Tian Yan Dynamic and Visual Assembly Instruction... of plastic deformation, the equipment used, and the process and characteristics of the final product [1], the final product quality and its assurance are affected by the interplay 4 M.W Fu and J Lu and interaction of all of these affecting factors, as shown in Fig 1 These factors include metal forming product design, material selection and property configuration, process determination and parameter... of the design conceptualization, the modelling and representation of the designed system is needed to be conducted In metal forming arena, mechanical, metallurgical and thermal phenomena and behaviours need to be represented from in the format of physical, mathematical and numerical models The physical model idealizes the real engineering problems and abstracts them to comply with certain physical theory... mechanical plastic and thermal behaviours and the interaction and interplay in-between the billet material and tooling Furthermore, the metal-formed part design, process determination and configuration, tooling design also affect the product quality To ensure the “right the first time design from product quality improvement perspective, all the affecting factors need to be investigated and their relationship... Evaporator Surface 111 S L Mahmood, N Bagha, M .A. R Akhanda, A. K.M.S Islam 3rd Order Double B-Splint Surfaces and the 3rd Order Contact in NC Machining 121 Guran Liu, Quanhong Liu, Dongfu Zhao, Deyu Song, Jingting Yuan The Research of Product and Project-based Aerospace Product Lifecycle Management 131 Haicheng Yang, Qing Su, Shikai Jing, Sanchuan Cheng, Miao He Application... Chen, Jin Lei Analysis and Optimization of Modal Characteristics of the Base of the Cartesian Robot 63 Lixin Lu, Guiqin Li, Huan You, Limin Li Numerical Analysis on the Temperature and Thermal Stress Distribution in Adhesive Joints 71 Ning Zhao, Leilei Cao, Hui Guo, Qingjian Jia and Jianjing Dai Kinematical Modeling for Main Machines and Integrating into Beverage Packaging Production .. .Advanced Design and Manufacture to Gain a Competitive Edge Xiu-Tian Yan • Chengyu Jiang • Benoit Eynard Editors Advanced Design and Manufacture to Gain a Competitive Edge New Manufacturing... issues related to the global advanced design and manufacture and recent industrial application papers with a goal towards bringing together design and manufacture practitioners from academics,... and S Sharma GA-based Automatic Test Data Generation for UML State Diagrams with Parallel Paths 147 C Doungsa-ard, K Dahal, A Hossain, T Suwannasart Chapter Materials Design and Processing