Neural network approach to grading maintainability of wet areas in high rise buildings

CHAPTER INTRODUCTION 1.1 BACKGROUND The importance of recognizing and assessing the total costs of owning, constructing, operating and managing buildings is being increasingly realized throughout the developed world [1] Quality costs in the construction industry as a whole are relatively high in terms of total project costs The bulk of this project costs are attributed to the building’s operation and maintenance costs during its lifespan [2-3] It is imperative to understand the degradation processes of buildings, to define methods and tools in order to easily identify potential defects (at design stage, as well as in servicing stage) and to find solutions to reduce their effects and to avoid any unforeseen cost for repair or maintenance Premature failures cause an enormous waste of resources [4] The life cycle cost of buildings, as a matter of fact, has a big weight over gross world product [4]: o Building activities represent approximately 40% of the world production o Solid waste production from building construction, demolition and the production of building products approximately represent 40% of the world waste production Chapter Introduction Moreover, building failures approximately generate 10% of that life cycle cost [4] Thus failure prevention could have very substantial effects both on the direct costs of a building and the environmental impact of construction sector, in every country It is of the utmost importance to design for durability and maintainability of buildings and their products With this in mind, it should be of primary interest to adopt a life cycle cost (LCC) perspective to building maintenance management Buildings that are managed with rational and long-term perspective will remain attractive for a longer time period and the need for replacement will be lessened As buildings are getting more technically complex with an increasing number of installations and equipment, these installations usually have shorter life spans than the building itself It is suspected that this would increase maintenance costs compared to older buildings due to the accelerated aging of components and installations This implies that components might have to be replaced even before the end of their technological lifespan This replacement can contribute to a sharp increase in operation and maintenance costs which in turn increases the total building life cycle costs Coupled by the lack of structured objective condition rating system, and means of analyzing and reporting key building information, it is impossible to simultaneously assess current conditions accurately, project future conditions, and track building performance [5] or even building costs Therefore, key building components cannot be properly evaluated, nor can deficiencies be identified When defining the maintenance Chapter Introduction needs of a building, interaction between components is difficult to evaluate, therefore work may not be effectively planned, budgeted, and accomplished Very often, maintenance managers lack the resources to appropriately inspect and appraise facilities This lack of information has resulted in reliance on building managers to only identify and document work needs The management has thus become reactive instead of proactive; where maintenance works are primarily dictated by the incidences of building component failures and the demands of end-users [5] Thus, there are increasing demands made on the maintenance management to provide tools that would support maintenance plans and provide quantitative means for the prediction of the service life of the various building components at different levels of performance [6] This dissertation would provide the impetus to spearhead serious considerations and create a momentum for the Singapore construction industry to incorporate maintainability issues into the design stage 1.2 JUSTIFICATION OF STUDY Extensive work and research have been conducted to improve the maintainability of buildings in many countries [7-14] The blueprint for the Singapore construction industry –Construction 21 highlights the importance of enhancing building maintainability For greater efficiency, the life cycle of Chapter Introduction project, from design to construction to maintenance, should be seen in totality It recognized that the higher costs of maintenance of such buildings is often hidden and not considered when assessing the cost of the construction project Benchmarks that can be used to audit maintenance costs and produce manuals which give the design life and maintenance costs of components were deem to be desirable [15] Wet areas is one that poses great threats to the maintenance budget of buildings The annual maintenance expenditure for residential and office buildings in Singapore accounts for $35/m2 and $87/m2 respectively [16] Defects in wet areas such as toilets and bathrooms have caused inconvenience to the users and are aesthetically unpleasant Compounded by poor construction workmanship to provide watertightness, difficulties in maintenance have contributed to increasing number of occurrence of defects in wet areas Maintenance managers are becoming painfully aware of the lack of knowledge and tools in their organizations to assist in effectively carrying out any planned maintenance The management could only react to anomalies, which are the pre-acknowledgement of defects, when the defects became obvious In order to accomplish building maintenance in such a scenario, ad hoc maintenance seems to be the next best approach Consequently, the funds needed to repair even the simplest defect would increase several folds [5] Further, when major components eventually fail, repair work may be deferred due to budget constraints In the short term, Chapter Introduction this process is self-defeating despite meeting the maintenance needs, as long-term goals are not achieved in this resource-constrained environment [5] These deficiencies call for a more holistic and total approach to design; embracing the entire construction process, explicitly addressing maintainability during the service life [17-22] and a more aggressive approach to whole life cycle costing; to assess the cost performance and to propose more economical alternatives [22-24] The evaluation of building maintainability should be a methodological approach whereby the different measurements of defined variables are analysed to trace the causal relations between the measures and the specific defects There should be in place a maintainability assessment model for the evaluation of whole life performance; with regards to the important parameters of determining the ease of maintenance, right from the start of the project development stage There are many reasons why it is important to develop a predictive maintainability model: to spearhead the incorporation of maintenance issues into consideration during design stage, to establish a benchmark by which the maintainability of wet areas can be measured and compared, Chapter Introduction to serve as a tool for the prediction of maintenance costs related to wet areas over the building’s lifespan 1.3 RESEARCH PROBLEM The level of maintainability of a building is proportional to its life cycle cost expenditure, to keep it in optimum performance If the building is not maintainable and defects are recurring, more money has to be spent to restore buildings to near original conditions which consequently impose more cost burdens to the total life cycle cost of building With large amount spent on the maintenance of buildings each year, prudent examination of influencing factors of design, construction and maintenance is necessary [9, 25-28] With merits of a maintainability model for wet areas highlighted above, it is necessary to develop a modeling technique to improve design and construction practices in the building industry with an aim to prolong the whole life performance of wet areas and minimize maintenance costs Further reasons to push ahead with the construction of maintainability model include the following First, though wet areas not constitute a large area of a building, the maintenance costs spent on wet areas alone can be as high as 50% of a building’s maintenance costs [29] Thus it is essential to identify the important parameters that would influence the aesthetic and functional performance of wet areas Chapter Introduction Secondly, very few attempts have been made on improving maintainability of buildings by considering maintenance issues at the design stage If such issues can be thoroughly dealt with during the inceptual stage, decisions made during design stage would have greatest effects to prolong the performance in wet areas Thirdly, the model would assist in deducing the important design parameters to derive optimum design layout that would facilitate maintenance within the scarce maintenance budget The use of a more superior neural network model is to ensure all possible underlying non-linear patterns are captured This derived model would aid designers by giving more weight to the various parameters that would influence the future level of maintainability of wet areas 1.4 RESEARCH OBJECTIVES The main aim of this study is to develop a predictive model that will help designers and clients to incorporate maintenance issues into the conceptual stage and to predict one part of the future maintenance costs of wet areas which apparently constitute a large portion of building maintenance costs The objectives of the study are: To determine common defects and their sources; Chapter Introduction To identify the various parameters contributing to the defects which undermine the performance of wet areas and increase the maintenance cost of wet areas; To construct a robust neural network model to predict the maintainability of wet areas 1.5 RESEARCH HYPOTHESIS This research has set forth to critically examine that a neural network based model can effectively predict the level of maintainability of wet areas On this basis, a research hypothesis that can serve to guide the entire study may be suitably stated as follows: “Prediction of level of maintainability of wet areas can be facilitated by the use of neural network based model” 1.6 SCOPE OF WORK A thorough literature review of relevant published books, past dissertations, journals, research digest and other related articles on the issues of the maintenance issues of wet areas was conducted Through this review, a better understanding on the theoretical aspect of the study and current status of the maintenance field in the industry can be achieved Condition surveys were conducted to determine the types and extent of the common defects in different building types and their causes Types of Chapter Introduction defects from the relevant establishments, building managers, repair contractors and case studies were also collated to determine the common defects in non-residential buildings Analysis of defects and identification of factors affecting maintainability of wet areas Development and validation of the model Scope of works Literature review of articles on maintainability and related fields Analysis of defects Construction of inputs to model Condition surveys and consultation with industry specialists Construction of predictive model Validation Figure 1.1 Scope of works 1.7 ORGANISATION OF THESIS (Figure 1.2) Chapter one gives brief background on the importance of building maintenance in the construction value chain In the local industry one of the building elements, which effects high maintenance costs, is the wet areas Thus the issue of enhancing maintainability of Chapter Introduction wet areas through modeling maintainability using neural network was emphasized in this chapter, which takes the form of a statement of the research problem A concise illustration of the research objectives and work scope would also be included A conceptual review of issues of building lifecycle, building performance and building maintenance which lead to the notion of improving building maintainability was highlighted in Chapter two A review of risk management was also included to set the foundation for use as the approach to this research An evaluation of two commonly used forecasting techniques of multiple linear regression and artificial neural network seeks to justify the choice of using the more superior neural network to model wet area maintainability Chapter three presented the research methodology This served to guide the conduct of this research and a concise flow of the development of the thesis Chapter four presented common defects in wet areas as assessed from the building samples Photos and self-drawn diagrams would be provided to facilitate the comprehension of underlying mechanisms of the defects This would provide sufficient evidence to substantiate the development of the various influencing factors of maintainability 10 Table 7.5: Sample cases Case Case Case Case Case Case Case Waterproofing selection very low very low very low very low very low very low very low Waterproofing detail very low very low moderate very low moderate low very low Plumbing selection very low moderate moderate very low very low very low moderate Plumbing detail moderate moderate moderate moderate moderate moderate moderate Plumbing maintenance high very low moderate high high moderate very low Fitting selection very low very low low low low very low very low Fitting design very low very low very low very low good very low very low Fitting maintenance very low very low very low very low very low very low very low Ventilation very low very low moderate very low very low moderate very low Material durability low low low low low very low low Material sustainability low low low low low moderate low Material maintainability very good low very good very low very low very low very low Usage low low low low very high low low Construction workmanship very low very low very low very low very low very low very low Maintenance practices low very low very low very low very low very low very low MS 100 81 85 97 88 91 99 Chapter Results and discussion 223 Parameters Chapter Results and discussion 7.5 MODEL VALIDATION WTH CASE STUDIES Three case studies of schools, office and industrial buildings were carried out to ascertain the accuracy of the model with actual site assessments Table 7.6 Comparison of MS between predicted and actual cases Parameters Case 1(School) Model Onsite generated interview Case (Office) Model Onsite generated interview Case (Industrial) Model Onsite generated interview Waterproofing selection 5 5 5 Waterproofing detail Plumbing selection Plumbing detail Plumbing maintenance Fitting selection Fitting design Fitting maintenance Ventilation Material durability Material sustainability Material maintenance usage Construction quality Maintenance 5 5 3.4 5 5 3 3 3 3 5 3 5 5 5 4.5 5 5 5 4.06 3.85 5 5 4.26 3.85 3 4.26 3.6 3 5 5 5 4.86 3.5 4.99 3.5 4.69 5 89 80 94 90 71 75 MS 224 Chapter Results and discussion Performing the correlation test using SPSS 11.0, a correlation value of 1.000 at 0.00 significance level was achieved for all the three cases This demonstrates the feasibility of using the model to predict future maintainability of wet areas in buildings 7.6 SUMMARY This chapter describes the results and observations made during the implementation and validation of the proposed system as well as some observations made from the results collated from the questionnaire Two major indices of approximation error and generalization error are commonly used to measure the performance of neural network based applications According to the results, the proposed model showed a low approximation error and a slightly higher generalization error This proved the model to be robust and effective for use Sensitivity analysis shows that materials performance, waterproofing selection and sanitary fitting design are among the significant factors affecting the maintainability of wet areas 225 CHAPTER CONCLUSIONS AND RECOMMENDATIONS 8.1 INTRODUCTION The life cycle of buildings have a big influence over the economy as well as in the environment Failure prevention therefore has enormous beneficial effects on both the direct costs and the whole life cycle costs of buildings and their components Far from declining, both the frequency and severity of building failures, especially in wet areas in the tropics are on the increase Given that millions of dollars spent on maintenance each year, it is of compelling logic and is imperative to reduce such costs to a minimum This can only be done, if maintenance issues are seriously considered right from the design stage, where intentions to design for durability and maintainability are put forth The study has developed from the condition surveys of 450 buildings and in-depth assessment of 120 buildings, intensive interviews and field studies carried out with various building specialists, 16 important risk factors affecting the level of maintainability of wet areas 226 Chapter Conclusions and Recommendations 8.2 SUMMARY The importance of building maintainability in achieving minimum resources wastage and increase in productivity is emphasized in Chapter One One of the building elements affecting high maintenance costs is wet area To effectively minimize maintenance costs for wet areas, the chapter sets out a proposition to adopt a cause and effect approach to model wet area maintainability using artificial neural networks Chapter two provides a conceptual foundation to building maintenance and building performance and lifecycle cost The cause and effect approach takes on a risk management application to determine wet area maintainability An evaluation of two commonly used forecasting techniques of multiple linear regression and artificial neural network was also included to justify the use of a more superior neural network to model wet area maintainability Chapter three presents the research methodology of this research This serves to guide the conduct of this research and a concise flow of the development of the thesis Computational formulae were derived for specific parameters of construction quality and material durability where all possible technical specifications were taken into consideration as described in Chapter five 227 Chapter Conclusions and Recommendations Chapter four presents common defects in wet areas as assessed from the building samples Diagrams were included to provide clear illustration of the defect cases This provide the learning platform of past errors and good practices which further substantiate the development of 16 various influencing factors of maintainability Influencing parameters of design, construction, material selection, maintenance, microenvironment and building profile, which have adverse effects on the maintainability of wet areas, were intricately discussed in Chapter Technical knowledge elicited from the specialists interviewed Illustrations of good practices were included to as benchmarks to good designs of wet areas Implementation of the neural network model was documented in Chapter six The quantification of identified parameters was established based on a wide literature review, surveys and interviews from the various industry participants Chapter seven discusses the empirical findings of the research and the validation of the derived neural network model Results were displayed to illustrate the predictive power of the model The more influencing factors would be identified via a sensitivity test analysis They are differentiated from the others using the mean squared error value Results from case studies carried out were illustrated to prove the feasibility of using the model for future prediction of wet areas maintainability 228 Chapter Conclusions and Recommendations 8.3 IMPORTANT FINDINGS The research is executed in accordance to the objectives stated in chapter one: 1) To determine common defects and their sources in wet areas; 2) To identify the various parameters contributing to the defects which thus undermine the performance of wet areas and increase the maintenance cost of wet areas; 3) To construct a robust neural network model to predict the maintainability of wet areas The objectives set out as mentioned above seeks to approach and take maximum advantage of errors committed during design, construction, maintenance, of current buildings and from the ensuing defects, lessons could be learnt to reduce the incidence and their effects The objectives were fulfilled and concluded as below: The study has identified in depth the common types of wet area defects that occur in 120 non-residential buildings The more common defects are: (1) mastics failure (23%), (2) staining of tiles (19%), (3) cracking/ debonding of tiles (19%), (4) water leakage through cracks (6%) and (5) paint defects (6%) These causes of the defects occur mainly due to design deficiencies (11%), construction (42.9%), maintenance (9.2%) and material 229 Chapter Conclusions and Recommendations (36.6%) The identification of these common defects bring about the research with substantial evidence to determine the various design, construction, maintenance and material details that would influence the maintainability of wet areas 16 influencing parameters identified to have great impact on the maintainability of wet areas are waterproofing selection, waterproofing details, plumbing selection, plumbing details, plumbing maintenance, fitting selection, fitting details, fitting maintenance, ventilation, material durability, material maintainability, material sustainability, usage, construction workmanship, maintenance practice, age These 16 parameters were used as inputs to construct the neural network model for maintainability of wet areas The novel attempt to construct a grading device for wet areas, using artificial neural network has proven to be realistic and robust for use for office, school and industrial buildings A low approximation error of 0.001 and slightly higher generalization error of 0.005 obtained from the model demonstrated the high accuracy of representing an unknown function and high capability in generalizing for unseen inputs Gradings for wet areas in typical office, school and industrial buildings were found to be 92, 87 and 83 respectively The sensitivity analysis demonstrated that waterproofing selection (MSE = 0.8426), fitting selection (MSE= 0.6903), material durability 230 Chapter Conclusions and Recommendations (MSE=0.9971), material sustainability (0.9981), material maintainability (MSE=1.030), are among the significant factors determining the maintainability of wet areas Three cases studies performed to validate the robustness of the model were carried out Results gave a strong correlation between the predicted values and the actual site assessed values of correlation coefficient value of 1.00 at 0.00 significance level Having minimum risks of those factors, wet areas in industrial, office and school building could demonstrate fairly high level of maintainability Optimum maintainability of wet areas is identified to be dependent on the synergistic combination of components with a view to compatibility and optimality so as to fulfill intended functionality, economy and maintainability in use 8.4 CONTRIBUTION This research contributes in the following areas: 1) Collate the common problems in wet areas in schools, offices and industrial buildings and identify sources of defects This would serve to provide evidence to the occurrence of defects and their failure paths 2) Explore important building design, materials, construction, maintenance and microenvironment parameters which would affect the achievement of maintainability of wet areas 3) The use of artificial neural networks in constructing the maintainability model for prediction of wet areas would effectively be a reliable decision-enhancing tool for 231 Chapter Conclusions and Recommendations designers in achieving the ease of maintainability of wet areas in terms of real cost values It provides an effective alternative to aid the designers to focus on details that would have great impact on the performance of the wet areas as a whole system, which thus enable reduction of resource wastages and low productivityvalue maintenance work right from the design stage 8.5 RESEARCH OUTPUT Arising from the research are also papers submitted/accepted to the following conferences and journals: 1) “Maintainability of Buildings in the Tropics”- Conference paper to International Workshop on Management of Durability in the Building Process This paper focuses on maintainability of buildings in the tropics in two areas: façade and wet areas The mounting costs of maintenance are attributed to the persistent occurrence of defects, which could be well illustrated from the webbased defects library (www.hpbc.bdg.nus.edu.sg) compiled for this study It is hence necessary to improve the level of maintainability right from the design stages In addition to defect library, a manual illustrating the performance of materials under tropical conditions and two grading systems derived from artificial neural network were presented The systems allowed complete evaluation of alternative designs, materials, construction and maintenance 232 Chapter Conclusions and Recommendations practices, so as to achieve best possible solutions of technical attributes that can lead to minimum life cycle maintenance cost 2) “Designing for Maintainability”- Conference paper to 2nd International Symposium on Building Pathology, Durability and Rehabilitation “Learning from Errors and Defects in Building” Comprehensive condition surveys of 450 tall buildings and in-depth assessment of a further 120 tall buildings and face-to-face interviews with the relevant building professionals were carried out to examine façade and wet areas failures and their causes Through learning from past errors, the paper advocates the use of grading systems based on artificial neural network to enhance decision-making on issues of maintainability right from the design stage This system would serve as a practical tool for owners, facility managers, designers and contractors to achieve optimum solutions of technical attributes that lead to minimum life cycle maintenance cost, right from the conceptual and design stages 3) “Multivariate approach to the prediction of maintainability of wet areas”Construction Management and Economics A regression model to predict the maintainability of wet areas was developed The model was derived from comprehensive condition surveys, interviews with 233 Chapter Conclusions and Recommendations professionals and defect analysis of 96 buildings The study showed that plumbing selection, access for fitting maintenance, material maintainability, usage, construction workmanship are the most significant parameters associated with the maintainability of wet areas 4) “Defect Analysis of Wet Areas in High-rise Buildings” - Construction and Building Materials This paper discusses some important findings from a research project on the maintainability of wet areas of high-rise non-residential buildings The implications of six key factors of maintainability namely water-tightness, spatial, integrity, ventilation, material and plumbing on the occurrence of 14 most common defects found in wet areas were evaluated Problem areas evaluated include water leakage from ceiling, staining/discoloration, paint defects, cracking/spalling of concrete, cracking/debonding of tiles, fungi/algae growth, pipe leakage and corrosion 5) “A Review of Building Maintainability-State of the Art”- Journal of Architectural Engineering This paper reviews the issue related to maintainability of building and discusses works of researchers worldwide The paper offers two approaches that could be integrated with the concepts of maintainability to augment building performance throughout its economic life The two approaches are 1) total quality approach via 234 Chapter Conclusions and Recommendations performance audit 2) life cycle cost (LCC) approach Various systems constructed to enhance quality delivery and maintainability of buildings was also discussed An attempt to integrate building performance and life cycle cost in Singapore to improve the maintainability of buildings was presented 6) “Artificial Neural Network Approach for Grading of Maintainability in Wet Areas of High-rise Buildings” – International Journal of Architectural Science Review A grading system using artificial neural networks to enhance decision-making of wet area design was developed The model was derived from condition survey of 450 tall buildings and in-depth assessment of a further 120 tall buildings and interviews with the relevant building professionals The system allows comparison of various alternative designs, materials, construction and maintenance practices, so as to achieve optimum solutions of technical attributes that lead to minimum life cycle maintenance cost 7) “Selection of Durable Materials in the Tropics” - Structural Repair With increasing complexity in the building construction trend and the advancement of building material technology, more building materials and substitutes have evolved and adopted for use to function together in a building that 235 Chapter Conclusions and Recommendations is supposed to maintain its technical performance during its intended working life This paper presents an indicative computational method for the durability of building materials for facades and wet areas in the tropics Total operations and maintenance costs of the identified materials are also included to provide suggestive maintenance expenditure over the materials’ service life 8) “Façade Maintainability and determining its significant risk factors under tropical conditions: an ANN approach ”- Construction Management and Economics A model to assess the maintainability of façade using neural network techniques was developed Inputs were derived from comprehensive studies of 600 tall buildings through detailed field evaluation and interviews with professionals in the whole building delivery process Sensitivity analysis showed that the most significant factors associated with façade maintainability include the system selection, detailing, accessibility and material performance 8.6 RECOMMENDATIONS This study is conducted based on non-residential buildings A further and detailed research can be done to include residential buildings where the level of usage, maintenance and types of materials used are different from this study A better 236 Chapter Conclusions and Recommendations representation of the building cluster in the market could be achieved and the sample size enhanced to improve the prediction capacity of the model The scope of studies can also be expanded to other parts of the buildings, such as basement, façade and roof Maintainability grading system can be established for each building element and an overall total maintainability index of building could be developed Main indices employed in this research include design, material selection, construction and maintenance Other parameters such as customer satisfaction and the core competencies of the maintenance staff should be factored into the maintainability model This would enable the maintainability model to take into consideration the direct effects of maintenance on the activities taking place in the building such as reliability of equipment to fulfil functional requirement of the occupants Competent maintenance staff is an important factor that determines the efficiencies of maintenance work in the building 237 [...]... in maintaining them A brief introduction to the concept of building pathology is also provided A brief review of risk management is included as the approach in evaluating maintainability, where the subject in view is “achieving high level of maintainability and the various risk sources are design, construction, maintenance, microenvironment and building profile 2.2 MAINTAINABILITY The concept of maintainability. .. parameters influencing the performance of areas over the building lifespan In this thesis, the first attempt to construct a novel maintainability model, using artificial neural network, to spearhead continued improvement in area of building maintenance is presented This first initiative deals with internal wet areas The thesis describes how the neural network can be used to predict the level of maintainability. .. set of scalars providing points to an underlying maintainability function k = the expected performance ∫ ( Risk ) = mix of risk attributes Maximize performance M Maaiinnttaaiinnaabbiilliittyy Minimize risk Minimize cost Figure 2.1: Function of maintainability 16 Chapter 2 Literature review 2.3 MANAGEMENT OF RISK IN MAINTAINABILITY Grading of the maintainability requires the exploration of the underlying... workmanship [9] and incompetent maintenance practices [13] 15 Chapter 2 Literature review This trend is due to the growing complexity of buildings, such as increasing proportion of systems in them, higher levels of service requirements, and the higher portion of maintenance costs added to the life cycle costs of buildings Thus to address the issue of maintainability in totality, the marriage of building performance... with the growing demand in buildings The fragmented nature of building and construction process is found to be the 19 Chapter 2 Literature review main contributing factor [7, 68-73] However, building defects may be an issue only if they are major or excessive [73] To effectively improve the ease of maintainability, it is of a compelling logic to examine in great details the bane to maintainability -persistent... Research Methodology o Design of questionnaire o Data collection o Grading system Chapter 4: Defects Analysis o Common types of defects o Sources of defects Chapter 5: Factors affecting maintainability of wet areas o Design, construction, maintenance parameters Chapter 6 Implementation of Neural Network o Sets out guidelines for the training of model o Ranking criteria of factors Chapter 7 Results and... chalking, peeling and flaking paint, blistering, staining, rust stains and algae and fungus growth [88] 2.5.3 Water leakage Chew and De Silva has expressed in two papers that water leakage is one of the most common defect in wet area [29,71] The factors affecting watertightness include improper application of waterproofing at penetrations and incorrect fixing of discharge pipes including lack of proper... of appropriate programmes of remedial works, and monitoring and evaluation of remedial works in terms of their functional, technical and economic performance in use Understanding the principle and the practical application of building pathology could assist all interested building parties to achieve total building maintainability 31 Chapter 2 Literature review 2.7 MAINTAINABILITY MANAGEMENT Improving... the construction industry has been inclined towards the development of techniques in order to extend service life of existing structures, rather than drawing up measures to ensure maintainability of buildings A Condition Assessment Score is formulated [16] as a means to prioritize maintenance expenditure A Condition score of 1 to 6 is assigned to building components after systematic investigations Scores... [33] The notion of maintainability has been manifesting during the past decades as building owners demand more durable buildings The issue of maintainability thus has grown to paramount importance, as owners are confronted with soaring maintenance costs [2, 6 28, 34-39] These lofty maintenance costs can be reflected in the increasing number of defects attributed to deficiencies of design [14, 27], ... costs of buildings Thus to address the issue of maintainability in totality, the marriage of building performance and building life cycle cost is of importance The term maintainability of buildings. .. of building maintainability with respect to building performance of wet areas and the building life cycle cost involved 14 Chapter Literature review in maintaining them A brief introduction to. .. value chain In the local industry one of the building elements, which effects high maintenance costs, is the wet areas Thus the issue of enhancing maintainability of Chapter Introduction wet areas