The Application of Lean Construction to Reduce Waste in Construction Flow Process

The Application of Lean Construction to Reduce Wastes in Construction Process Flow

by

TAN WEE LENG

Thesis submitted in fulfilment of the requirements for the award of the Degree of Master of Science (Project Management)

School of Housing, Building & Planning, Universiti Sains Malaysia 2004

i ACKNOWLEDGEMENT

I would like to express my greatest gratitude to my research supervisor Dr. Mohd Wira Mohd Shafiei for his mentor and encouragement during the whole process of preparing this thesis. I would like to thank my family and friends who were always there for me whenever in needed the most. Special thank to my employer, Mr. Chew Hock Jin who supported and tolerated me throughout my whole Master program in USM, to my sister Lee Kheng who helped my in my SPSS analysis, and last but not least, to all the respondents who took part in completing and returned the questionnaires for this research.

Without all of you, this thesis would not be existed in the first place. Thanks a lot.

Regards, Tan Wee Leng April 2004

ii ABSTRCT

There are a lot of non-value adding activities or wastes in construction practices and many among those were left unnoticed or unattended. Previous studies have shown that there were significant amounts of values loss due to construction process flow wastes and tremendous productivity improvements can be achieved by simply targeting at reducing or eliminating those wastes and/ or improve the process flow. This thesis was conducted on the basis to study the waste concepts and the level of “leanness” in local construction practices based on philosophies and principles drawn by Lean Construction. A quantitative survey was carried out through structured questionnaires over a randomly selected group of managerial personnel in construction activities. The results from the study show that the respondents have a relatively low recognition over contributory time wastes group compared to direct conversion wastes group and non-contributory time wastes group as categorised in the study. The correlation analyses also show almost no significant inter-relationships between wastes recognition and wastes controlled, wastes recognition and wastes occurrence frequencies, and wastes controlled and wastes occurrence frequencies for those 3 waste categories (except 1 negative significant case are recorded on waste recognition vs. waste controlled for contributory time wastes). This has suggested that a very high level of subjectivity possessed by the respondents on recognising, controlling and witnessing the actual occurrence of construction wastes where majority cases are recorded with nonconsistent pairs relationships. In this study, a cluster of waste cause variables have also been examined against their likelihood to impact on the construction processes as well as relating those variables directly to specific construction wastes. This will serve as a good exercise to expose the root sources to particular construction wastes. In conclusion, the outcomes of the research suggested that there still have rooms for construction process improvements with the application of lean construction and proper waste concepts instilled to all level of construction personnel and processes.

iii CONTENT PAGE

pp. Acknowledgement

i

Abstract

ii

Abstrak

ii (a)

Content Page

iii

List of Tables

vi

List of Figures

viii

List of Appendixes

x

1) Chapter 1: Introduction 1.1) Research background 1.2) Problem statement 1.3) Research aim 1.4) Research objectives 1.5) Research scopes 1.6) Research limitations 1.7) Research methodology 1.8) Research significance 1.9) Thesis structure 1.10) Summary

1 3 4 5 6 7 8 11 12 14

2) Chapter 2: The Problems in Construction and The Trends in Improvement Strategies 2.1) Introduction 2.2) Problems in construction 2.3) Manufacturing as source of references and innovations 2.4) Emergency of new production philosophy in manufacturing 2.5) The concept of new production philosophy 2.6) The impacts of new production philosophy in construction 2.7) The impact of new production philosophy in Malaysia construction industry

15 17 18 20 24 25 28

iv pp. 3) Chapter 3: The Concepts of Production and The Principles Behind New Production Philosophy 3.1) Introduction 3.2) The concept of production 3.2.1) Transformation concept 3.2.1.1) Core principle of transformation concept 3.2.1.2) Critiques on transformation concept 3.2.2) Flow concept 3.2.2.1) Core principle of flow concept 3.2.3) Value generation concept 3.3) Main ideas and techniques of new production philosophy 3.3.1) Just In Time (JIT) 3.3.2) Total Quality Control (TQC) 3.3.3) Other related concepts 3.4) Principles of new production philosophy 3.5) Flows in construction production 3.6) Challenges of implementing Lean Construction

31 31 32 32 34 35 36 37 40 40 41 42 45 57 59

4) Chapter 4: The Concepts of Waste and Modeling Construction Wastes and Performances 4.1) Introduction 4.2) Construction waste in general 4.3) Waste and value loss in construction activities 4.3.1) Waste and value loss due to quality of works 4.3.2) Waste and value loss due to constructability 4.3.3) Waste and value loss due to material management 4.3.4) Waste and value loss due to non-productive time 4.3.5) Waste and value loss due to safety issues 4.4) New concept of waste in Production Activities 4.5) Underlying the waste concepts in construction 4.6) Waste classification 4.7) Key construction waste causes 4.8) Modeling waste and performance in construction

59 59 64 64 65 66 66 67 67 71 75 81 85

5) Chapter 5: Research Methodology 5.1) Introduction 5.2) Method of research 5.3) Profile of respondents 5.4) Structures of questionnaire 5.5) Score assignment 5.6) Analysis methods

90 90 95 96 97 98

v pp. 6) Chapter 6: Data Analysis and Interpretation 6.1) Introduction 6.2) Descriptive analysis results 6.2.1) Respondents and their organisation’s background 6.2.1.1) Position of respondents 6.2.1.2) Nature of work of respondents 6.2.1.3) Main core construction projects involved by the respondent’s organisation 6.2.1.4) CIDB registration grade of the respondent’s companies 6.2.1.5) Main project clients 6.2.2) Respondent’s waste perceptions and control actions 6.2.2.1) Analysis on direct conversion wastes 6.2.2.2) Analysis on non-contributory time wastes 6.2.2.3) Analysis on contributory time wastes 6.3) Inferential analysis results 6.3.1) Correlation among direct conversion wastes concepts and perceptions, waste event control and frequencies of waste event occurrences 6.3.2) Correlation among non-contributory time wastes concepts and perceptions, waste event control and frequencies of waste event occurrences 6.3.3) Correlation among contributory time wastes concepts and perceptions, waste event control and frequencies of waste event occurrences 6.3.4) Ranking on frequencies of occurrences for wastes exist in construction processes 6.3.5) Ranking on likeliness for sources/ causes for the construction wastes 6.4) Causes and Effects Matrix 7) Chapter 7: Conclusions and recommendations 7.1) Introduction 7.2) Discussion of the findings of the research 7.2.1) Relating the research findings to research objectives 7.2.2) Rewritten hypotheses and interpret the results 7.3) Limitations of the research 7.4) Challenges in implementing Lean Construction

103 103 105 106 107 107 108 109 110 110 117 124 131

131

133

135 137 139 141

145 145 145 149 153 154

Reference

xi

Appendices

xiv

vi

vi LIST OF TABLES

pp. Breakdown of scopes covered in each phase of the research

9

Table 1.2:

Contents summary for the chapters covered in this thesis

12

Table 2.1:

Waste in construction: Compilation of existing data

16

Table 2.2:

Context of manufacturing and construction production

19

Table 5.1:

Waste elements in 3 separate waste group

93

Table 5.2:

Waste causes factors group

94

Table 6.1:

Construction waste recognition under direct conversion waste category

111

Construction waste control practices under direct conversion waste category

113

Matrix table between waste concepts and control practices for direct conversion wastes

115

Construction waste recognition under non-contributory time waste category

118

Construction waste control practices contributory time waste category

120

Table 1.1:

Table 6.2:

Table 6.3:

Table 6.4:

Table 6.5:

Table 6.6:

Table 6.7:

Table 6.8:

Table 6.9:

under

non-

Matrix table between waste concepts and control practices for non-contributory time wastes

122

Construction waste recognition under contributory time waste category

125

Construction waste control practices under contributory time waste category

127

Matrix table between waste concepts and control practices for contributory time wastes

129

vii pp. Table 6.10:

Correlation Pearson-r results summaries for hypothesis 1, 2 and 3

Table 6.11:

Correlation Pearson-r results summaries for hypothesis 4, 5 and 6

134

Correlation Pearson-r results summaries for hypothesis 7, 8 and 9

136

Table 6.13:

Construction waste variables ranking

137

Table 6.14:

Sources/ causes of construction waste ranking

139

Table 6.12:

132

viii LIST OF FIGURES

pp. Figure 1.1:

Research methodology flow chart

Figure 3.1:

Hierarchical decomposition of production process with transformation concept

33

Figure 3.2:

Production as a flow process

37

Figure 3.3:

The conceptual scheme of a supplier-customer pair

38

Figure 3.4:

Simplified diagrams categorizing the principles of lean production for production improvement

56

Figure 3.5:

The preconditions for a construction task

58

Figure 4.1:

Performance improvement in conventional, quality and new production philosophy approaches.

69

Figure 4.2:

Koskela’s flow process model.

72

Figure 4.3:

Serpell’s Modeling of the construction process

72

Figure 4.4:

Categories of wastes of productive time

80

Figure 6.1:

Composition of respondent’s position

105

Figure 6.2:

Percentage of categorisation of respondent’s nature of work

106

Figure 6.3:

Composition of the main core construction projects by the respondent’s company

107

Figure 6.4:

CIDB registration of the respondent’s company

108

Figure 6.5:

Percentages of main project clients of the respondent’s company

109

Figure 6.6:

Breakdown of direct conversion waste recognition cases

112

Figure 6.7:

Breakdown of direct conversion waste event control cases

114

8

ix pp. Figure 6.8:

Breakdown of non-contributory time waste recognition cases

Figure 6.9:

Breakdown of non-contributory time waste control practice cases

121

Figure 6.10:

Breakdown of contributory time waste recognition cases

126

Figure 6.11:

Breakdown of contributory time waste control practice cases

128

Percentage breakdown of the wastes recognition by nature of work of the respondents

130

Figure 6.12:

119

Figure 6.13:

Causes and Effects relationship for the cases of major causes (Categorised)

142

Figure 6.14:

Causes and Effects relationship for the cases of others causes (Categorised)

143

x LIST OF APPENDICES

pp. xiv Appendix 1:

Correlation Pearson r results from SPSS 10.0

Appendix 2:

One way t-test results from SPSS 10.0

xv

Appendix 3:

SPSS data inputs sheets

xvi

Appendix 4:

Causes and Effects matrix tables

xxii

Appendix 5:

Sample of questionnaires

xxiv

1 CHAPTER 1

INTRODUCTION

1.1 Research background

Construction is a key sector of the national economy for countries all around the world, as traditionally it took up a big portion in nation’s total employment and its significant contribution to a nation’s revenue as a whole. However, until today, construction industries are still facing numbers of contingent problems that were bounded to be resolved since the past time. The chronic problems of construction are well known such as Low productivity, poor safety, inferior working conditions, and insufficient quality. (Koskela, 1993) and the phenomenon of the poor performance and conditions in construction had long been witnessed and recorded by academics and practitioners throughout the world regardless in developed countries e.g. England (Eaton, 1994) or in developing countries e.g. Chile. (Serpell et al., 1995)

Nowadays, increasing foreign competition, the scarcity of skilled labour and the need to improve construction quality are the key challenges faced by the construction industry. Responding to those challenges imposes an urgent demand to raise productivity, quality and to incorporate new technologies to the industry. A lack of responsiveness can hold back growth, and to development of the needed infrastructure for the construction industry and other key activities in the country. (Alarcón, 1994)

2

Pertaining to the challenges faced by the construction industry, numerous researches and studies had been carried out for the past decades to identify the causes to the construction problems and some of them had went on to suggest and recommend solutions to rectify those identified problems. The early phase of these studies mainly focused on the “end” side of the construction process with the introduction of new technologies and equipment to speed up the construction process and improve overall productivity. It was only until late 1980s where a new construction improvement movement was being initiated by looking into the “mean” side of the construction process-related problems in a more holistic and structured way based on the philosophy and ideology of lean production. With the lean construction paradigm, construction industry had started to be reviewed and evaluated in the possibilities of implementing these new lean perspectives of production concepts in the construction processes to optimise the overall construction performance on construction stage as well as design stage. However, in construction, there has been rather little interest in this new production philosophy. (Alarcón, 1994) This matter laid on whether or not the new production philosophy has implications for construction and will give any significant impacts on the productivity improvement.

According to the scholars and researchers in Lean Construction, the new construction production philosophy is laid on the concepts of conversion and flow process. Therefore, performance improvement opportunities in construction can then be addressed by adopting waste identification/ reduction strategies in the flow processes in

3 parallel with value adding strategies with the introduction of new management tools and with proper trainings and education programs. Unfortunately, these new lean construction concepts especially those on wastes and values most of the times are not well understood by construction personnel. Particularly, waste is generally associated with waste of materials in the construction processes while non-value adding activities such as inspection, delays, transportation of materials and others are not recognised as waste. (Alarcón, 1995) As the result of that, the productivity of construction industry cannot be fully optimised due to the narrow interpretation on the concept of waste current adopted. In this case, substantial education programs need to be arranged for all related parties involved in order to implement the new process improvement strategies successfully throughout the construction process cycle.

1.2 Problem statement

It is presumably that construction industries in Malaysia are facing the same generic (process-related) problems/ wastes on construction activities which was also faced by their counterparts regardless those in developed countries or developing countries. However, the main problem in Malaysia (might be the same for most of other countries) is the lack of clear indicators on quantitative parameters to assess the extent of those problems/ wastes to have been impacted on the overall performance and productivity of local construction industries. To date, there have not been many well-documented quantitative studies and records on to process-related problems/ wastes which arisen on construction site in Malaysia. As a result of that, the introduction of the concepts and

4 framework of new lean construction ideology are seen as an opportunity to address the existing problems in local construction industry and utilising concepts and framework of new lean construction ideology can then go further to formulate the extent of impacts of those problems/ wastes on a more structured and quantitative basis.

Prior to assess the severity of the process-related problems/ wastes which existed in the construction processes for the local construction industries, the differentiate of traditional and new production/ construction concepts will have to be drawn prior to further investigation and evaluation on any project performances. New measurement parameters such as waste, value, cycle time or variability that was not covered under traditional concepts are to be introduced into this study as accordance to the lean construction ideologies and the subjects in this case; the local construction personnel will be subsequently examined with those new parameters to review the level of understanding and practicability in local construction industry compare to the requirements and the concepts set forth by lean construction philosophy.

1.3 Research aim

This research is intended to verify and reevaluated the status of existing productivity and performances on construction activities and processes for local construction industries. This is meant to have a clearer picture on how “lean” is local construction industry performed currently under the compilation of new measurement parameters on

5 particularly on waste and cycle time pertaining to the concepts and principles of Lean Construction.

In line with this, this research will intend to reveal the perception of the local contractors by seeing waste recognition and reduction as strategies in improving construction productivity. This will be an important factor to be evaluated as the key factors of the success for the practice of lean construction improvement strategies mostly based on the mind set and readiness of the practitioners mainly personnel with the leading role in the cycle of the construction projects to drive the whole program.

1.4 Research objectives

The research seeks to confirm four (4) objectives, which are:

1. Examine the general perceptions of the local construction industry with the lean construction principles of practices. 2. Determine the degree of problems arisen from wastes identified in existing scenario and practices in local construction industry. 3. Identify the source of wastes (classified under lean construction) and related them to the waste identified in local construction industry. 4. Study the potential project productivity improvements by reducing and eliminating the wastes as classified under lean construction.

6 1.5 Research scopes

The scopes of the research are as follows:

1. The area of this study is confined to the Peninsular of Malaysia excluding East Malaysia.

2. The primary data will be collected through questionnaires mainly through postal and electronic mailing to selective group of respondents (mainly site personnel who has a leading role in the construction management e.g. project managers, general managers, resident engineers, site managers, site engineers and supervisors, etc) for the construction and consultant firms in the confined area of study.

3. The conducted sample surveys are not to be considered as a specific case in depth but to capture the main characteristics of the population using a fixed sample. Thus, there will be no limitation imposed to the qualification level and working experience of the respondents.

4. The primary data collection is conducted from XX th November 2003 until XXth February 2003. The returned completed questionnaires that received during the designated period will be analysed and the responses beyond this time frame will be ignored.

7 1.6 Research limitations

There are certain limitations to this research as the writer wish to highlight as follow:

1. Research Validity

The study approach for this research is based on structured surveys to be carried out based on postal and electronic mailing questionnaires. Therefore, the feedback from the respondents will provide as a sole dependable source of result in supporting the research finding. Field data collections for all the local construction projects will very much help in verifying the feedback from the structured surveys but due to time constraints and the insignificant of field data collections to support the research finding, field data collections is discarded from the research design and it is recommended that in the future, further studies on the field to be carried out as a collective efforts to justify the finding of this research.

2. Research Reliability

As mentioned early, the concepts of lean construction are relatively new in Malaysia, thus there might be little attention given by the local construction industry to the area of parameters or variables need to be measured and evaluated. This might affects the consistency of the results in the data measurement where the subjectivity of answering from the respondents is required.

8

1.7 RESEARCH METHODOLOGY

FORMULATE PROBLEM STATEMENT First Stage RESEARCH OBJECTIVES

RESEARCH SCOPES

RESEARCH DESIGN

Second Stage

DATA COLLECTION & PROCESSING Third Stage

PRIMARY DATA

Fourth Stage

Fifth Stage

Sixth Stage

SECONDARY DATA

DATA ANALYSIS

CONCLUSION & EVALUATION

RESEARCH REPORT

Figure 1.1 Research methodology flow chart

9 First Phase q

Formulation

q

Problem Statement

In formulation of the problem statement for this study, extensive preliminary literature studies are required as the areas of study are relatively new in Malaysia.

q

The concepts of “Lean Construction” need to be further explored and examined before forming the research aims, objectives and scopes

q

Sources of references will include journals, technical reports, proceedings, publishing on the Internet and books.

q

The research aims, objectives and scopes will then be established together with the discussion with the supervisor in order to formulate the direction of the research.

Second Phase q

Research Design

q

A quantitative research approach will be adopted for this study requiring the development and dissemination of a questionnaire survey.

q

A sample survey will be conducted through a randomly selected subject group throughout Peninsular Malaysia.

q

Questionnaires are to be properly designed and

10 structured. The factors and variables to be outlined and put into questions in a way that enable the quantitative data collected later will then be able to be tested according to pre-determined research objectives. Third Phase q

Data Collection &

q

Processing

The methods of data collection to be adopted includes: a. Postal questionnaires b. Email questionnaires

q

The data collected will then be properly organised prior to data analysis process

Fourth Phase q

Data Analysis

q

Statistical analysis will be carried out on the data collected via descriptive statistic and inference statistic.

q

The significant of the outlined factors and variables to be analysis against the research problem statement

q

SPSS (Statistical tool) will be utilised to analysis particular data to reach particular conclusion

11 Fifth Phase q

q

This phase will evaluate and conclude the results

Conclusion &

from the data analysis and conclude by answering

Evaluation

the research objectives with the findings from the data collected and analysed q

Attach with constructive recommendations for further researches

Sixth Phase q

Research Report

q

This will involved substantial submission of write up, orgainising the data format and outline

q

Constant discussion with the supervisor throughout the write up processes, until the approval of draft, Amendment draft and finally Final manuscript

Table 1.1 Breakdown of scopes covered in each phase of the research

1.8 Research significance

To the benefits of local construction practices, this research is set to be one of the pioneer efforts of instill the lean construction philosophy and principles into the practical application on local construction industry. Production weaknesses and problems of the industry will be redefined and reassessed in order to reformat a new strategy and plan for productivity improvement in the local construction practices.

12 Whereas academically, the compilation of this research was also intended to set up some frameworks for quantitative measurement on the productivity performances and wastes measurement for local construction industry and perhaps set ground for future researches to refine or reengineer the construction processes and practices of the local construction industry.

1.9 Thesis structure

CHAPTER

BRIEF CONTENTS

CHAPTER 1

This chapter covers the overall perspective for the research,

INTRODUCTION

such as research background, problem statement, research aims, objective, scope, methodology and limitation

The extensive literature review will be divided into three main chapter (chapter 2-4) as follows: CHAPTER 2

This chapter will focus on the following subjects:

THE PROBLEMS IN

q

CONSTRUCTION AND THE TRENDS IN

Examine the background of the problems existed in current construction processes

q

IMPROVEMENT

Study the trends of improvement strategies in construction

STRATEGIES

q

CHAPTER 3

This chapter will focus on the following subjects:

THE CONCEPTS OF

q

PRODUCTION AND THE PRINCIPLES

PHILOSOPHY

Theory of production and comparison of various types of production philosophy

q

BEHIND NEW PRODUCTION

Study the emergency of new production philosophy

Review the core of the lean ideology and the significant benefit of lean production practices

q

Review the challenges of implementing lean production philosophy into construction industry

13 CHAPTER 4

This chapter will focus on the following subjects:

THE CONCEPTS OF

q

WASTE AND NEW

Study the definition, concept and classification of waste based on lean construction

TOOLS OF MODELING

q

Outline the wastes in construction practices

CONSTRUCTION

q

Review some of the principles of construction process

WASTES AND

improvement and models of waste as suggested by the

PERFORMANCES

lean construction paradigm

CHAPTER 5

This chapter will focus on the questionnaire design e.g. the

RESEARCH

formulation of the hypotheses and the ways those hypotheses

METHODOLOGY

are to be tested with the factors and variables identified in the questionnaire. A general overview on the statistical concepts will be studied to ensure the data are analysed accordingly and to generate the data outputs relevant to the hypotheses formulated.

CHAPTER 6

This chapter processes, analyses and then interprets the result

DATA ANALYSIS AND

collected from the field survey and to stand out the aims and

INTERPRETATION

objectives for this research

CHAPTER 7

This chapter concludes the whole study based on the

CONCLUSIONS AND

findings. The tested hypotheses will be related to the

RECOMMENDATIONS

research objectives and further interpreted and conclusion on the achievement of the research objectives will be drawn. Some recommendations will also be drawn from the findings and the limitation during the research period will also be highlighted

Table 1.2 Contents summary for the chapters covered in this thesis

14

1.10 Summary

This research is conducted based on the criterions discussed above to reevaluated the status of existing productivity & performances and the perception of waste concepts for Malaysia construction industries based on lean construction concept and principles. The further explanation of each of the subsequent chapters as summarised in Table 1.2 is presented in the following chapters.

15 CHAPTER 2

THE PROBLEMS IN CONSTRUCTION AND THE TRENDS IN IMPROVEMENT STRATEGIES

2.1 Introduction

Construction industries worldwide have become notorious for under-performance in many aspects such as quality, safety, productivity and product delivery to planned budgets, programmes and client satisfaction. According to Adrain (1987), the construction industry in US has been rated among the worst industries in term of productivity improvement for the period between 1970 to 1986. The rate of productivity for US construction industry always performed lower than the annual total US productivity between the period of 1970 to 1986 as reported by U.S. Department of Commerce. Koskela (1993) also conducted a study to indicate the order of magnitude of non value-adding activities (waste) on various partial studies carried out in Sweden and US. From Koskela’s data compilation, it has shown that construction processes are characterised by high content of non value-adding activities leading to low productivity as shown in Table 2.1 below.

16

Waste Quality costs (non-conformance)

Cost 12% of total of project cost

Country US

External quality cost (during facility use) Lack of constructability Poor materials management Excess consumption of materials on site Working time used for non-value adding activities on site Lack of safety

4% of total project costs 6-10% of total of project cost 10% &12% of total of project cost 10% on average Approx. 2/3 of total time

Sweden US US Sweden US

6% of total project cost.

US

Table 2.1: Waste in construction: Compilation of existing data (Koskela, 1992)

Previous studies in the UK, Scandinavian countries, and US also reflecting the same scenario where the studies indicated up to 30% of construction is rework, only 40-60% of potential labour efficiency, accidents can account for 3-6% of total costs, and at least 10% of materials are wasted (DETR, 1998). The cost of rework in Australian construction projects has been reported as being up to 35% of total project costs and contributes as much as 50% of a project's total overrun costs. In fact, rework is one of the primary factors contributing to the Australian construction industry's poor performance and productivity. (Love et al, 2003)

In general, a very high level of wastes/ non added value activities are assumed to exist in construction and it is difficult to measure all waste in construction. Several partial studies from various countries have confirmed that wastes in construction industry represent a relatively large percentage of production cost. (Formosa, Carlos T et al, 2002). The existences of significant numbers of wastes in the construction have depleted overall performance and productivity of the industry and certain serious measures have to be taken to rectify the current situation.

17 2.2 Problems in construction

The chronic problems of construction are well known: low productivity, poor safety, inferior working conditions, and insufficient quality. (Koskela, 1993) However, most of the time, those critical problems of construction were left unattended because people of the industry refrained to believe or accept that there is a solution to those problems. According to Koskela (1992), the incapability to improve the productivity level of construction projects is mainly perceived by people in the industry as due to its peculiarities and special features: one-of-a-kind nature of projects, site production, and temporary multi-organisation. Most people concluded that its fragmented nature, lack of co-ordination and communication between parties, adversarial contractual relationships, and lack of customer focus inhibit the industry's performance.

Unlike manufacturing activities where the production activities are fundamentally governed and controlled under a rather routine process, construction activities are subjected to relatively wide range of variables and wastes factors throughout its information management and resource flow process as compared to manufacturing activities. These variables and wastes generated in construction activities are mainly due to its large fieldwork component, the provisional nature of some of its organisations, and its intensive use of labour and non-stationary equipment and indeed, those construction peculiarities and variables will restraint the efficiency of the construction processes compared to those stationary & well-controlled manufacturing processes, but all of those peculiarities and variables can be overcome with the application of new

18 flow design and improvements as well as new technologies adoption. (Alarcon, 1994) Therefore, the organisation, planning, allocation and control of these resources, processes and technologies are what finally determine the productivity that can be achieved.

2.3 Manufacturing as source of references and innovations

Throughout the years, manufacturing has always been a reference point and a source of innovations to construction. Several efforts had been made to transfer the successful techniques and solutions from manufacturing process into construction in order to relieve the problems in construction industry. Most of the early efforts involved new technology and process adoption from manufacturing practices i.e. industrialisation, prefabrication and modularisation (new process adoption) and computer integrated construction and automated construction (new technology adoption). However, there have been no signs of major improvements to construction has resulting from both trends of process dissemination and solutions as quoted by Koskela (2000). The main reasons behind the failure of achieving any major improvements from both trends are mainly due to certain key features between manufacturing and construction.

A comparison with manufacturing shows the key features, which distinguishes construction from manufacturing, is the extent of uncertainty evident throughout the production phase as shown in Table 2.2

19

Start of manufacturing production

Start of construction in the field

What How

Highly defined Highly defined. Operations plan is in great detail based on many trails. Primary sequence of many tasks is inflexible and the interdependencies are documented and analyzed. Positions in process determine required skills

Assembly Objectives

Produces one of a finite set of objects where details of what and how are known at the beginning of assembly Rapid learning during the first units preparing for production line

Evolving as means refines ends Partly defined but details un-examined. Extensive planning remains by hard logic but may change. Interdependencies due to conflicting measurements, shared resources, and intermediate products only partly understood. General craft skills to be applied in a variety of positions Make the only one. The details of what and how are not completely known at the beginning of assembly Rapid learning during both planning and early sub-assembly cycles

Improvement Strategy

Table 2.2 Context of manufacturing and construction production

However, there was a new development trend based on a new production philosophy derived from manufacturing was slowly caught the attentions of the academics and practitioners in construction industry in late 1980’s. In the last three decades have seen great improvements in performance in manufacturing. Lean industries now use less of everything: Less on the manufacturing space, less on the human effort in factories, less on the investment in tools and less on the product development time. In general, significant improvements in all performance indicators have been observed simultaneously in manufacturing industry. All these improvements have not been the product of a radical or sharp change of technology but the result of the application of a new production philosophy leading to “Lean Production”.

These new development trend stresses on the importance of basic theories and principles related to production management and now, the same practices have been progressively promoted as an ideal solution as improvement strategies for construction industry especially in waste reduction and elimination strategies. Among the earliest

20 academics promoting the new production philosophy in construction industry included Lauri Koskela and Luis F Alarcón. Koskela (1992) identified the overwhelming dominance of conversion thinking in construction and argues for replacing conversion model with a flow/ conversion model in order to reduce waste. Alarcon (1995) also pointed out that performance improvement opportunities could be addressed by adopting waste identification/ reduction strategies in parallel to value adding strategies. In other words, identifying and measuring waste will served as an effective way to assess the performance of any production systems because it will usually point out areas of potential improvement and the main causes of inefficiency. Waste measures are more effective to support process management, since they enable some operational costs to be properly modeled and generate information that is usually meaningful for the employees, creating conditions to implement decentralised control.

2.4 Emergency of new production philosophy in manufacturing

Traditional manufacturing production philosophy and practices from the earlier days of industrialisation era never went beyond the concept of the overall production process to be treated as a mean of transformation process only, and by ignoring the flow process has limited the full potential of process improvement. In 1950’s, those traditional manufacturing production system were set for a paradigm shift when Taiichi Ohno (1912-1990), a former Toyota (a Japanese major car manufacturer) executive had set out to develop a new production system called Toyota Production System. Ohno's original ideas were based on the adoption of production strategies identified according

21 to the demand of the downstream production chain, part of a production plan that ensured the planned pace was maintained throughout the production process.

The basic idea in the Toyota production system is the elimination of inventories and other waste through small lot production, reduced set-up times, semiautonomous machines, co-operation with suppliers, and other techniques and in other words, the idea was to achieve a continuous production flow by adopting monitoring measures for each process phase, aiming to reduce inventories. (Conte & Gransberg, 2001) The production philosophy behind Toyota production system is called Just-In-Time production (JIT) and throughout the years, it has remained among the core practices of the new production philosophy. Big productivity gains from Just-In-Time production (JIT) and later as lean production, had been reported from manufacturing since the end of 1970’s (Koskela, 2000)

Simultaneously, quality issues were attended to by Japanese industry under the guidance of American consultants like Deming, Juran and Feigenbaum. Quality philosophy evolved from a statistical method of quality assurance to a wider approach, including quality circles and other tools for company-wide development. These ideas were developed and refined by industrial engineers in a long process of trial and error; establishment of theoretical background and wider presentation of the approach was not seen as necessary.

22 However, the ideas on new production philosophy was not widely spread around the industry at the beginning stage, it only diffused to Europe and America starting in about mid 1970, especially in the automobile industry. Since the end of 1970’s, a lot of new approaches to production management have been introduced into manufacturing industry i.e. JIT (Just-In-Time), TQM (Total Quality Management), Time Based Competition, Value Based Management, and Concurrent Engineering. It turns out that for all the production management mentioned above were having the same common idea but only they were viewing it from more or less different angles.

In years, the general conception of the new production philosophy evolved through three levels: it was viewed as a tool (e.g. kanban and quality circles), as a manufacturing methodology (e.g. JIT and TQM) and as a general management philosophy (e.g. lean production) (Koskela, 1993). This common idea shared by a conceptualisation of production or operations in general; the different in view angle is determined by the design and control principles emphasized by any particular approach. (Koskela, 1993) For instance JIT stresses the elimination of wait times whereas TQM aims at the elimination of errors and related rework but both apply under the same conceptualisation of production and operation e.g. a flow of work, material or information.

In the beginning of the 1990’s, the new production philosophy, which is known by several different names (world class manufacturing, lean production, new production system) is the emerging mainstream approach. It is practiced, at least partially, by major

23 manufacturing companies in America and Europe. The new approach has also diffused to new fields, like customised production, services, administration, and product development. In recent years, this new production philosophy has been disseminated and diffused in other industries, and this includes the construction industry (Koskela 2000), in the meantime, the new production philosophy has been undergoing further development, primarily in Japan.

The latest development on new production philosophy now is closely integrated with the ideology of lean thinking aiming for a leaner production chain throughout every stage of the processes. The term “lean” was first used by John Krafcik, who was a master’s student at MIT in the mid-1980s and it refers to a general way of thinking and specific practices that emphasize less of everything – fewer people, less time, lower cost (Cusumano & Nobeoka, 1998). Womack and Jones, (1996) suggested that Lean Thinking provides production processes a way of specify value, line up value-creating actions in the best sequence, conduct these activities without interruption whenever someone requests them, and perform them more and more effectively. Freeman (1999) concurred that Lean Thinking is not just about cutting down wastes (wasted time, wasted effort and wasted materials) but it is also about putting on value and it involves focusing on the whole process; from the earliest design to final handover.

24 2.5 The concept of new production philosophy

The core of the new production philosophy is based on the conclusive understanding that all production systems are constituted of 2 main activities: Conversions and Flows (waiting, moving, and inspecting). In the new production paradigm, only conversion activities add value to the final product whereas flow activities do not; value is determined under the value stream of the customers with the satisfaction of their requirements and cost paid on the final product. Therefore, the primary objectives for process/ performance/ productivity improvement under the flagship of new production philosophy should be targeted separately. That can be done through the improvement of flow activities (through which the conversion activities are bound together) by primarily focusing on reducing or eliminating them and on the other hand, conversion activities should be focused on making them more efficient.

This has important implications for the design, control, and improvement of production processes, because according to Koskela (1992), traditional production management paradigm sees the whole process simply as a conversion of an input into an output that can be divided into sub-processes, which are also conversion processes. All activities have been treated as though they were value-adding conversions without separating from the flow processes. This has led to complex, uncertain and confused flow processes, expansion of non value-adding activities, and reduction of output value.

25 Based on the understanding of the production process can be consists of both conversion and flow activities, a generic process improvement plan based on new production philosophy can be derived from the study of Enton (1994) on lean productivity of construction professions. The first step to implement process improvement plan is by analysis and separation of conversions and flows activities. For conversions activities identified, those activities should be channeled into the quality cycles (Quality control, Quality assurance and Total Quality Management) to increase efficiency of value added conversions. Whereas, for flow activities, the approach should be consists of way of flows simplification (through Elimination, simplification and automation) in order to reduce or eliminate non-value added flow activities.

2.6 The impacts of new production philosophy in construction

In recent years, application of new production philosophy in construction are getting more and more popular especially in the developing countries i.e. US and Europe. Koskela (1992) identifies the overwhelming dominance of conversion thinking in construction and argues for replacing the conversion model with flow/conversion model in order to reduce waste. This has inspired Gregory Howell, a civil engineer, and Research Director Glen Ballard from Lean Construction Institute of Idaho began to investigate the performance of project planning systems. They later espoused the concept of "Lean Construction" by seeing a potential for applying the general principles set by Lauri Koskela (a researcher with VT Building Technology in Espoo) into construction. (Wright, 2000)

26

According to Lean Construction Institute, Lean Construction is a production management-based approach to project delivery; a new way to design and build capital facilities and it extends from the objectives of a lean production system; maximise value and minimise waste and to specific techniques and applies them in a new project delivery process. The application of lean production philosophy to construction – or Lean Construction, as it has been called by a group of collaborating researchers since 1993 (Koskela, 2000). Since then, the enthusiasms over lean construction paradigm are intensified and widely accepted practitioners and academics around the world under the belief that the implementation of Lean Construction will dramatically improve construction performance and labour productivity.

Nowadays in UK and US, Lean Construction philosophy and principles are gradually being introduced into universities’ mostly at post-graduate level. A lot of researches and case studies have already been carried out using lean construction theories and principles to formulate models and frameworks by the mean to evaluate the performance and productivity in various aspects of the construction industry. Flow improvement concepts and waste reduction/ elimination still remained major focus among those researches in which they are viewed as value enhancement to the whole construction production processes.

The development in UK’s construction industry eventually went onto an even higher level of implementation with the establishment a nationwide movement of “Rethinking

27 Construction”. The origins of Rethinking Construction lie in a landmark report published in 1998 led by Sir John Egan. As a report, it set clear targets for improvements in the construction industry in UK, supported the principles of Best Value and built upon the work of the 1994 Latham report. It has now matured and is becoming a positive force that will bring major change within the construction industry in UK.

The essences of Egan Report are nominally based on Lean Construction principles with the setting a number of year-on-year targets on the basis of promoting a continuous improvement in productive processes through a reduction of “waste” (time, cost, rework and accidents) and an increase in “value” (quality, improvements, finish products, etc) as shown below:

1. Reduce costs – capital by 10% 2. Reduce time – construction by 10% 3. Improve predictability – time and cost by 20% 4. Reduce defects – at handover by 20% 5. Increase productivity – by 10% 6. Increase profit and turnover – by 10% 7. Reduce accidents – by 20%

28 One of the example that Egan report impacts on construction industry in UK was a major shift to long-term partnering deals between architects and housing associations in UK following Department of the Environment, Transport & the Regions edict that social housing must be 100% Egan-compliant within four years periods. In the Housing Corporation's guide to allocation, a timetable sets out that the proportion of Corporation-funded building procured on Egan principles must be 10% in 2000/2001, rising to 30% in 2001/2002, 60% in 2002/2003, and reaching 100% in 2003/2004. That policy had forced the UK’s developing associations to a fast-track conversion of their procurement policies.

This radical shift in social housing procurement would have fundamentally altered the relationship between housing associations and architects in UK. Developing associations now have the Egan targets: 10% annual reduction in the cost and time of construction, a 20% increase in predictability, 20% reduction in defects and other standards for improvement. In this way, many UK’s housing associations will have to look for consultants who understand the design/build/project management process to achieve it for them.

2.7 The impact of new production philosophy in Malaysia construction industry

There have not been any significant signs of positive impacts of the new production philosophy in Malaysia construction industry either in national level or domestic level. The problems in Malaysia construction industry are still at a very serious level. For

29 example in construction safety, Abdul Rashid Abdul Aziz and Abdul Aziz Hussin (2003) has quoted on a recent construction safety study carried out in 2001. In their paper quoted that “the awareness of safety procedures and laws to be low among site operatives; both site operatives and main contractors exhibit apathy for safety; and safety enforcement is weak”. These phenomena of construction safety in Malaysia are also backed by the statistics on construction accidents rate published by from DOSH, which is also referred in their paper. This is only one dimension of problems in Malaysia construction industry and besides that, there was always news about delay on construction projects and low quality of project execution and delivery regardless private or public projects.

Academically, lean construction are not being considered as a main source of research direction in Malaysia, which is very much unlike countries like United Kingdom and United States where they have post-graduate studies specially focus on the research of lean construction. Literally, there were too few literature studies available under this research topic locally although some partial studies on material wastes only but not looking into the aspects of the construction process as a whole.

Institutionally, we have yet to witness any radical movements being planned towards achieving leaner and more efficient construction industries as a whole as such as what had been drafted in United Kingdom. This idea requires a throughout commitment and understanding over the entire construction industries in order to achieve those goals and the improvement over performance will be very significant.

30

Overall, the impacts of new production philosophy to local construction industries are still considered minimal and so in reverse the potential of improvement in this field is vast. Therefore, local construction industries need to be more aware of the new concepts, principles, tools and instruments behind this new lean construction philosophy. This is important efficient in order to make the local construction practices leaner, more effective and able to sustain their competitiveness edges over other compatriots in the industries inside or outside Malaysia.

31 CHAPTER 3

THE CONCEPTS OF PRODUCTION AND THE PRINCIPLES BEHIND NEW PRODUCTION PHILOSOPHY

3.1 Introduction

When we start to discuss about new production philosophy, lean production or even lean construction and their impacts on the production system, apparently, this would signify that the existing conventional production philosophy or concepts inherited numbers of deficiencies or problems which need to be rectified or overcome.

In this chapter, new production philosophy or lean production is to be examined in detail on various perspectives starting on the conceptual of production into the derivation of main and related ideas and techniques in new production philosophy, compressing the principles behind the new production philosophy and finally the practical implementation of new production philosophy in actual construction practices.

3.2 The concept of production

A historical analysis carried out by Koskela (2000) has revealed that there are three concepts of production where the conceptualisation of production can be grouped based

32 on the generation of transformation-flow-value model of production theory or simply as TFV model.

3.2.1. Transformation concept

Since the beginning of the 20th century, transformation concept has been the dominant theory of production, both in practice and research where production is conceptualised as a process of transformation or “a transformation of inputs to outputs”. Production management equates to decomposing the total transformation into elementary transformations and tasks, acquiring the inputs to these tasks with minimal cost and carrying out the tasks as efficiently as possible.

3.2.1.1 Core principle of transformation concept

The first core principle which has been used in conjunction with transformation concept stated that: The transformation process can be decomposed into subprocesses, which also are transformation process as reflected in Figure 3.1, of breaking up the total transformation (production process) into much smaller and more manageable transformations and eventually can be further breakdown into individual continual tasks.

33

Material, Labours

Subprocess A

Production Process

Products

Subprocess B

Source: Koskela, Lauri (2000). An Exploration towards a production theory and its application to construction

Figure 3.1 Hierarchical decomposition of production process with transformation concept

The second core principle of the transformation model is a general acceptance of independency principle that the cost of the total process can be minimised through minimising the cost of each sub-process. The key issue pertaining to this principle leads to the assumption that every sub-processes of a total process are independent from each other and therefore cost minimisation can be applied through focus on cost management in each operation, sub-process or department.

The third core principle formulated currently recommended that It is advantageous to insulate the production process from the external environment through physical or organisational buffering. This principle is related to the independence assumption from the second core principle as discussed above and

34 it reflects that the transformation process that is most important, and it is thus a requisite to shield it from the erratic conditions in the environment.

3.2.1.2 Critiques on transformation concept

Transformation concept is conventionally wide-accepted in term of production theory and practical was mainly due to its sufficient power to model reality, and excellent power of various tools derived from it to analysis and control production in an easy and simple way. However, its oversimplification in theory formulation by considering all processes are transformation activities tends to undermine the full optimum of efficiency and productivity for the production process. Below are some of the critiques as cited by Koskela (2000):

1. By focusing on conversions, the model abstracts away physical flows between conversions. These flows consist of moving, waiting and inspecting activities. In a way, this is a correct idealisation; from the customer point of view these activities are not needed since they do not add value to the end product. However, in practice, the model has been interpreted so that a) These non value-adding activities can be left out of consideration or b) All activities are conversion activities, and are therefore treated as valueadding.

35 2. The output of each conversion is usually variable, to such an extent that a share of the output does not fulfill the implicit or explicit specification for that conversion and has to be scrapped or reworked 3. The specification for each conversion is imperfect; it only partially reflects the true requirements of the subsequent conversions and the final customer.

3.2.2. Flow Concept

The flow view of production, firstly proposed by the Gilbreths (1922) in scientific terms, has provided the basis for JIT and lean production. This view was firstly translated into practice by Ford (1926); however, the template provided by Ford was in this regard misunderstood, and only from 1940’s onwards the flow view of production was properly developed in Japan, first as part of war production and then at Toyota. As a result, the flow view is embodied in JIT and lean production and the triumph of the JIT and lean production has practically proven the power of this conception.

The new production concept of flow was emerged apparently from the erroneous view of decomposition in the transformation model of production that is the intervals between transformations, which happen to be nontransformations activities. In flow concept, production is viewed as a flow, where, in addition to transformation, there are waiting, inspection and moving stages. Production management equates to minimising the share of non-

36 transformation stages of the production flow, especially by reducing variability. In this context, flow model is looking beyond transformation model by taking non-transformations activities into consideration as to improve overall flow efficiency.

3.2.2.1 Core principle of flow concept

The first core principle of this flow concept is the introduction of time as an input (or resource) in production and therefore the main focus is in the amount of time consumed by the total transformation and its parts by aiming for the production improvement at shortening of the total time of production. With the introduction of time also implies that production has to be conceived as a physical process and not only as an economic abstraction in cost terms.

The second core principle of the flow concept is that time is consumed by two types of activities in the overall production flow which are transformation activities and non-transformation activities. Gilbert (1922) categorised the nontransformation activities as transfer, delay and inspection as showed in Figure 3.2 and it is obvious that these non-transformation activities are unnecessary and the less of them is better and best if there are none of them.

37

Moving

Waiting

Processing A

Inspection

Moving

Waiting

Processing B

Inspection

Scrap

Scrap

Source: Koskela, Lauri (2000). An Exploration towards a production theory and its application to construction

Figure 3.2 Production as a flow process

There are 3 main principles in production system design, control and improvement utilising flow concepts as shown below and they are seen to be centering over a common basic goal, which is eliminate waste from flow process. 1.

The first principle is to reduce the share of non-value-adding activities (waste),

2.

The second principle is to reduce lead time and variability

3.

The third principle provides practical ways in implementation such as simplify by minimising the number of steps, parts and linkages, increase flexibility and increase transparency.

3.2.3 Value Generation Concept

The value generation view was initiated by Shewhart (1931) and further refined in the framework of the quality movement but also in other circles. The value

38 generation concept are formulated not a same as transformation and flow concept by incorporating customer as the ultimate value determinate to the production and argued that the goal of production is to satisfy customer needs. In this case, value generation concept covers external needs and to ensure the internal physical process can generate appropriate values to the customer/ enduser. Figure 3.3 will illustrate the conceptual scheme of a supplier-customer pair and introduces the customer and product with its features. It is clear from the framework that it is not the transformation itself that is valuable, but the fact that the output corresponds to the requirements, wishes, etc of the customer which is valuable instead.

Requirements, expectations Supplier

Customer

Value through products and services

Source: Koskela, Lauri (2000). An Exploration towards a production theory and its application to construction

Figure 3.3 The conceptual scheme of a supplier-customer pair

This third concept of value generation concept views production as a means for the fulfillment of customer needs. Production management equates to translating these needs accurately into a design solution, and then producing products that conform to the specified design. It focus on control of the transformation and flow, namely control for the sake of the customer and it is important to highlight

39 that the value generation concept does not focus on any particular aspect of physical production like transformation and flow model do but rather on its control in securing value generated for the customer.

In this circumstances, conventional production philosophy would referred to production system is merely based on transformation concepts while new production philosophy would engulf both flow concepts and value generation concepts in the development of production system. The most significant differences between conventional and the new production philosophy can be discussed in two areas: conceptualisation of production and focus of improvement. For conventional production philosophy, production is perceived as consists of conversions only with all the activities in the processes are regarded as value adding, and the focus of process improvement only will happen by implementing new technology into the activities.

Whereas for new production philosophy, production is perceived as consists of conversions and flows where activities in the processes can be divided into value adding and non-value adding activities, therefore the focus of process improvement can be broken down into 2 separated areas which are the elimination or reduction for non-value adding activities and the increase of process efficiency for value adding activities through continuous improvement and new technology.

40 3.3 Main ideas and techniques of new production philosophy

Several factors make it difficult to present a coherent overview of the ideas and techniques of the new production philosophy. This is because this field is still relative young and in constant evolution where new concepts emerge and the content of old concepts change. The same concept is used to refer to a phenomenon on several levels of abstraction. It is not clear where to place the boundaries between related concepts. However, the overview over two historically important “root” terms, Just In Time (JIT) and Total Quality Control (TQC) can help to enhance the understanding of the basic concepts for new production philosophy, while other related newer concepts, which are primarily outgrowths of JIT and TQC. These outgrowths show that the field of application of the original ideas has extended far beyond the production sphere.

3.3.1 Just In Time (JIT)

The starting point of the new production philosophy was in industrial engineering oriented developments initiated by Ohno and Shingo at Toyota car factories in the 1950’s. The driving idea in the approach was reduction or elimination of inventories (work in progress). This, in turn, led to other techniques that were forced responses to coping with fewer inventories: lot size reduction, layout reconfiguration, supplier cooperation, and set-up time reduction. The pull type production control method, where production is initiated by actual demand rather than by plans based on forecasts, was introduced.

41

The concept of waste is one cornerstone of JIT. The following 7 wastes were recognised by Shingo as (1) Overproduction, (2) Waiting, (3) Transporting, (4) Too much machining (overprocessing), (5) Inventories, (6) Moving, (7) Making defective parts and products. Elimination of waste through continuous improvement of operations, equipment and processes is another cornerstone of JIT.

3.3.2 Total Quality Control (TQC)

The starting point of the quality movement was the inspection of raw materials and products using statistical methods. The quality movement in Japan has evolved from mere inspection of products to total quality control. The term total refers to three extensions:

1. Expanding quality control from production to all departments, 2. Expanding quality control from workers to management, and 3. Expanding the notion of quality to cover all operations in the company.

The quality methodologies have developed in correspondence with the evolution of the concept of quality. The focus has changed from an inspection orientation (sampling theory), through process control (statistical process control and the old seven tools Fishbone Diagram, Control Chart, Pareto Chart, Run Graphs, Histogram, Flow charts or Check sheets & Correlation Diagram),

to continuous process improvement (the new seven tools - Affinity

Diagram, Interrelationship Diagraph, Tree Diagram, Matrix Diagram, Prioritisation Grid, Process

42 Decision Programme Chart & Activity Network Diagram),

and presently to designing quality into

the product and process (Quality Function Deployment).

3.3.3 Other related concepts

Many new concepts have surfaced from JIT and TQC efforts. These have been rapidly elaborated and extended, starting a life of their own. Several of these concepts are described below.

1. Total Productive Maintenance (TPM)

Total Productive Maintenance is a comprehensive program to maximise equipment availability in which production operators are trained to perform routine maintenance tasks on a regular basis, while technicians and engineers handle more specialised tasks. The scope of TPM programs includes maintenance prevention (through design or selection of easy-to-service equipment), equipment improvements, preventive maintenance, and predictive maintenance (determining when to replace components before they fail).

TPM tackles the "six big losses" and is closely tied to the practices of 5S, the six big losses are: 1. Breakdown losses 2. Setup & Adjustment losses 3. Idling & minor stoppages

43 4. Reduced speed losses 5. Start up losses 6. Quality defects

2. Concurrent engineering

Concurrent engineering is a cross-functional, team-based approach in which the product and the production process are designed and configured within the same time frame, rather than sequentially. Ease and cost of constructability, as well as customer needs, quality issues, and product life cycle costs are taken into account earlier in the development cycle.

The main ideas about concurrent engineering is to achieve an improved design process characterized by rigorous up-front requirements analysis, incorporating the constraints of subsequent phases into the conceptual phase, and tightening of change control towards the end of the design process.

3. Continuous improvement

Continuous improvement is a never-ending effort to expose and eliminate root causes of problems; small-step improvement as opposed to big-step or radical improvement. A Continuous Improvement strategy involves everyone from the

44 very bottom to the very top, the basic premise being that small regular improvements leads to a significant positive improvement over time.

The main goal of the continuous improvements is to affect the mindset as well as achieve the improvements of the techniques. In this case, everyone pitches in and receives training in the appropriate skills; responsible for their own efforts, areas and progress of their teams and the employees will continuously suggest improvements to meet quality, cost and delivery target improvements. The key idea of continuous improvement is to maintain and improve the working standards through small, gradual improvements.

4. Visual management

Visual management is an orientation towards visual control in production, quality and workplace organisation. The core principal of visual management is the ability to understand that, with a quick look at the shop floor what orders are being done, if production is ahead, on par or behind and what needs to be done next. No orders are missed or lost and every one knows if they are behind or ahead on the day’s production. Shop floor staff will take on more self-managing responsibility with this method as day-to-day decisions are handled on the shop floor.

45 Generally this method is implemented on large boards next to particular areas on the shop floor, and as much information is shared as is feasible, ranging from maintenance to production targets and production output to injuries.

5. Re-engineering

Re-engineering is the radical reconfiguration of processes and tasks, especially with respect to implementation of information technology. The key issue in reengineering is in recognising and breaking away from outdated rules and fundamental assumptions in order to establish a radical change to the processes and tasks for improvement.

6. Value based strategy (or management)

Value based strategy (or management) is a customer-oriented, in contrast to competitor-oriented approach toward overall production process. It is a continuous improvement to increase customer by conceptualizing and articulating value as the basis for competing.

3.4 Principles of new production philosophy

In various subfields of the new production philosophy, a number of heuristic principles for flow process design, control and improvement have evolved. According to Koskela

46 (1993), there was ample evidence that through these principles, the efficiency of flow processes in production activities can be considerably and rapidly improved.

Many of those principles are closely related, but not on the same abstraction level. Some are more fundamental, while others more application oriented. It is also important to note that the understanding of these principles is of very recent origin. It is presumed that knowledge of these principles will rapidly grow and be systematised. The principles of new production were further breakdown as follows (Koskela, 1992)

1. Reduce the share of non value-adding activities

Reducing the share of non value-adding activities is regarded as the most fundamental principle of new production philosophy or lean production where it is the center of idea for new production philosophy, which differentiates it from conventional production thinking.

There are 3 main sources of non value-adding activities: 1. Non value-adding activities exist by design in hierarchical organisations. Every time a task is divided into two subtasks executed by different specialists, non value-adding activities increase: inspecting, moving and waiting. In this way, traditional organisational design contributes to an expansion of non valueadding activities.

47 2. Ignorance is another source of non value-adding activities. Especially in the administrative sphere of production, many processes have not been designed in an orderly fashion, but instead just evolved in an ad hoc fashion to their present form. The volume of non value-adding activities is not measured, so there is no drive to curb them. 3. Non value-adding activities exist also due to the nature of the production: workin-process has to be moved from one conversion to the next, defects emerge, accidents happen.

With respect to all three causes for non value-adding activities, it is possible to eliminate or reduce the amount of these activities. However, this principle cannot be used simplistically. This is because some of the non value-adding activities produce value for internal customers, like planning, accounting and accident prevention. Such activities should not be suppressed without considering whether more non value-adding activities would result in other parts of the process. However, accidents and defects, for example, have no value to anybody and should be eliminated without any hesitation.

Most of the principles presented below address suppression of non value-adding activities. However, it is possible to directly attack the most visible waste just by flowcharting the process, then pinpointing and measuring non value-adding activities.

2. Increase output value through systematic consideration of customer requirements

48

This is another fundamental principle. Value is generated through fulfilling customer requirements, not as an inherent merit of conversion. The organisational and control principles of the conventional production philosophy have tended to diminish the role of customer requirements. In many processes, customers have never been identified nor their requirements clarified. The dominant control principle has been to minimise costs in each stage; this has not allowed for optimisation of cross-functional flows in the organisation.

The practical approach to this principle is to carry out a systematic flow design, where customers are defined for each stage, and their requirements analysed. Other principles, especially enhanced transparency and continuous improvement, also contribute to this principle.

3. Reduce variability

Production processes are variable. There are differences in any two items, even though they are the same product, and the resources needed to produce them (time, raw material, labor) vary from time to time. From the customer point of view a uniform product is better. Thus, reduction of variability should go beyond mere conformance to given specifications and reduction of variability within processes must be considered an intrinsic goal.

49 The practical approach to decreasing variability is made up of the well-known procedures of statistical control theory. Essentially, they deal with measuring variability, then finding and eliminating its root causes. Standardisation of activities by implementing standard procedures is often the means to reduce variability in both conversion and flow processes. Another method is to install fool-proofing devices (“poka-yoke”) into the process as been introduced by Shingo in Toyota Production System.

4. Reduce the cycle time

Time is a natural metric for flow processes and it can be used to drive improvements in both cost and quality. A production flow can be characterised by the cycle time, which refers to the time required for a particular piece of material to traverse the flow.

The basic improvement rationale in the new production philosophy is to compress the cycle time, which forces the reduction of inspection, move and wait time. In addition to the forced elimination of wastes, compression of the total cycle time also provides faster delivery to the customer, reduced need to make forecasts about future demand, decrease of disruption of the production process due to change orders and establish easier management because there are fewer customer orders to keep track of.

Practical approaches to cycle time reduction include the following:

50 1. Eliminating work-in-progress (this original JIT goal reduces the waiting time and thus the cycle time) 2. Reducing batch sizes 3. Changing plant layout so that moving distances are minimised 4. Keeping things moving; smoothing and synchronising the flows 5. Reducing variability 6. Changing activities from sequential order to parallel order 7. Isolating the main value-adding sequence from support work 8. Decrease organisational layers and empowering the persons working directly within the flow

In general, solving the control problems and constraints preventing a speedy flow.

5. Simplify by minimising the number of steps and parts

One fundamental problem of complexity is extra cost incurred. If other things are being equal, the very complexity of a product or process increases the costs beyond the sum of the costs of individual parts or steps. Another fundamental problem of complexity is reliability: complex systems are inherently less reliable than simple systems. Furthermore, the human ability to deal with complexity is bounded and easily exceeded.

Simplification can be understood as 1. Reducing of the number of components in a product

51 2. Reducing of the number of steps in a material or information flow Simplification can be realised, on the one hand, by eliminating non value-adding activities from the production process, and on the other hand by reconfiguring valueadding parts or steps. Organisational changes can also bring about simplification. Vertical and horizontal division of labor always brings about non value-adding activities, which can be eliminated through self-contained units (multi-skilled, autonomous teams).

Practical approaches to simplification include: 1. Shortening the flows by consolidating activities 2. Reducing the part count of products through design changes or prefabricated parts 3. Standardising parts, materials, tools, etc. 4. Decoupling linkages 5. Minimising the amount of control information needed.

6. Increase output flexibility

At first glance, increase of output flexibility seems to be contradictory to simplification. However, according to some studies, many companies have succeeded in realising both goals simultaneously. Some of the key elements are modularised product design in connection with an aggressive use of the other principles, especially cycle time compression and transparency.

52

Practical approaches to increased flexibility include: 1. Minimising lot sizes to closely match demand 2. Reducing the difficulty of setups and changeovers 3. Customising as late in the process as possible 4. Training a multi-skilled workforce.

7. Increase process transparency

Lack of process transparency increases the propensity to err, reduces the visibility of errors, and diminishes motivation for improvement. Thus, it is an objective to make the production process transparent and observable for facilitation of control and improvement. The goal to achieve process transparency is to substitute self-control for formal control and related information gathering and this can be achieved by making the

process

directly observable

through

organisational

or

physical

means,

measurements, and public display of information.

Practical approaches for enhanced transparency include the following: 1. Establishing basic housekeeping to eliminate clutter: the method of 5-S (Sort, Set, Shine, Standardise, Sustain)

2. Making the process directly observable through appropriate layout and signage 3. Rendering invisible attributes of the process visible through measurements

53 4. Embodying process information in work areas, tools, containers, materials and information systems 5. Utilising visual controls to enable any person to immediately recognise standards and deviations from them 6. Reducing the interdependence of production units (focused factories).

8. Focus control on the complete process

There are two causes of segmented flow control: the flow traverses different units in a hierarchical organisation or crosses through an organisational border. In both cases, there is a risk of suboptimisation.

There are at least two prerequisites for focusing control on complete processes. First, the complete process has to be measured and secondly, there must a controlling authority for the complete process. Several alternatives are currently used. In hierarchical organisations, process owners for cross-functional processes are appointed, with responsibility for the efficiency and effectiveness of that process. A more radical solution is to let self-directed teams control their processes. For inter-organizational flows, long-term co-operation with suppliers and team building have been introduced with the goal of deriving mutual benefits from an optimised total flow.

54 9. Build continuous improvement into the process

The effort to reduce waste and to increase value is an internal, incremental, and iterative activity that can and must be carried out continuously. There are several necessary methods for institutionalising continuous improvement: 1. Measuring and monitoring improvement. 2. Setting stretch targets (e.g. for inventory elimination or cycle time reduction), by means of which problems are unearthed and their solutions are stimulated 3. Giving responsibility for improvement to all employees; a steady improvement from every organisational unit should be required and rewarded. 4. Using standard procedures as hypotheses of best practice, to be constantly challenged by better ways. 5. Linking improvement to control: improvement should be aimed at the current control constraints and problems of the process. The goal is to eliminate the root of problems rather than to cope with their effects.

10. Balance flow improvement with conversion improvement

In a situation where flows have been neglected for decades, the potential for flow improvement is usually higher than conversion improvement. On the other hand, flow improvement can be started with smaller investments, but usually requires a longer time than a conversion improvement.

55 The crucial issue is that flow improvement and conversion improvement are intimately interconnected as better flows require less conversion capacity and thus less equipment investment and vice verse more controlled flows make implementation of new conversion technology easier. However, it is often worthwhile to aggressively pursue flow process improvement before major investments in new conversion technology. Later, technology investments may be aimed at flow improvement or redesign.

11. Benchmark

Unlike technology for conversions, the best flow processes are not marketed to us; we have to find the world class processes ourselves. Often benchmarking is a useful stimulus to achieve breakthrough improvement through radical reconfiguration of processes and by means of it, fundamental logical flaws in the processes may be unearthed.

The basic steps of benchmarking include the following: 1. Knowing the process; assessing the strengths and weaknesses of subprocesses 2. Knowing the industry leaders or competitors; finding, understanding and comparing the best practices 3. Incorporating the best; copying, modifying or incorporating the best practices in your own subprocesses 4. Gaining superiority by combining existing strengths and the best external practices.

56

In summary, we can see that these principles of new production philosophy or more precisely lean philosophy are mainly revolving around improvement over flows of the processes. There is not much concern about the transformation or conversion concepts while the concepts of value are rather integrated into enhancing value to flows activities and not so much on the value of the products itself. The dimensions of the principles can be further grouped into three ideas for flows improvement that are flow compression, flow dynamic and flexibility and flow stability and control. Figure 3.4 simplified the principles of lean production for production improvement

Principles of lean production for production improvement

Flow Compression q Reduce share of non value-adding activities q Reduce variability q Reduce the cycle time q Simplify by minimising the number of steps and parts

Flow Dynamic & Flexibility q Increase output value q Increase output flexibility q Increase process transparency q Benchmarking

Flow Stability & Control q Focus control on the complete process q Build continuous improvement into the process q Balance flow improvement with conversion improvement

Figure 3.4 Simplified diagrams categorizing the principles of lean production for production improvement

57

3.5 Flows in construction production

The production in construction is of assembly-type, where different material flows are connected to the end product. In construction, there are 3 types of flows as suggested by Koskela (2000): material flow (the transportation of components to the site for particular installation), location flow (e.g. one particular trade goes through the different part of the building or construction site to get their work done) and assembly flow (e.g. the sequential of works of assembly and installation).

There are at least seven resource flows (or preconditions) that unite to generate the construction task as illustrated In Figure 3.5 below. Many of these resource flows are of relatively high variability, and thus the probability of a missing input is considerable. For example, it is not uncommon that detailed drawings are still lacking at the intended start of the work. Latent errors in drawings will emerge as problems during construction on site. External conditions also form one specific source of variability. The productivity of manual labour is inherently variable, and the availability of space and connecting works is dependent on the progress of tasks of previous trades, thus bound to be variable. Thus, in comparison to the typical manufacturing. Construction productions are subjected to more sources of variability and the insight gained is that construction consists of assembly tasks involving a high number of input flows. Planning and controlling production becomes very important and tasks and flows have to be considered in parallel in production management because: “realization of tasks

58 heavily depends on flows, and progress of flows in turn is dependent on realization of task” (Koskela, 2000)

Construction design

Components and materials

Workers

Equipment

Task

Space Connecting works

External conditions

Figure 3.5 The preconditions for a construction task (Koskela, 2000)

In construction actually it is the installation team that moves from location to location. This leads to another important feature of construction. In factory production, one part can physically be only at one workstation at any one time. However, in construction, several work units or trades can work on one part (e.g. a room) simultaneously at the same time with lessened productivity due to interference and congestion of space of operation. Thus, this phenomenon of congestion has a more dramatic influence on construction productivity especially at workstation congestion and not so much of part congestion, which is common in manufacturing.

59 CHAPTER 4

THE CONCEPTS OF WASTE AND MODELING CONSTRUCTION WASTES AND PERFORMANCES

4.1 Introduction

In general, in lean production and lean construction paradigm sees that all those activities that produce cost, direct or indirect, but do not add value or progress to the product can be called waste. Waste is measured in terms of costs, including opportunity costs. Other types of waste are related to the efficiency of the processes, equipment or personnel and are more difficult to measure because the optimal efficiency is not always known.

In this chapter, we will look into the definition, concept and classification of waste based on new production philosophy and lean construction and outline the different researches on wastes in construction practices and review some of the principles of construction process improvement and some models of wastes and performance in construction as suggested by the lean construction paradigm.

4.2 Construction waste in general

Waste in the construction industry has been the subject of several research projects around the world in recent years. However, Most studies tend to focus on the waste of materials, which is only one of the resources involved in the construction process. This

60 seems to be related to the fact that most studies are based on the conversion model, in which material losses are considered to be synonymous of waste. Formosa, et al (2002) stated that many people in the industry have considered waste are directly associated with the debris removed from the site and disposed of in landfills and they suggested that the main reason for this relatively narrow view of waste is perhaps the fact that it is relatively easy to see and measure. The main focus for those conventional material waste studies in construction are seen to be restricted to physical waste or material waste in construction and/ or the specific impacts due to the physical waste itself.

Formoso, et al. (1999) in their earlier research paper entitled “Method for Waste Control in Building Industry” had significantly grouped some researches and studies done by other researchers around the world on the wastes in construction into 2 main aspects based on the impacts of the construction waste:

1. Researches and studies mostly focused on the impacts on environmental damage that result from the generation of material waste. For example: a) The research on construction waste conducted by The Hong Kong Polytechnic and the Hong Kong Construction Association Ltd. In year 1993 aimed to reduce the generation of waste at source, and to proposed alternative methods for treatment of construction waste in order to reduce the demand for final disposal areas. b) The research project conducted by Brossik and Brouwers in The Netherlands year 1996, concerned with the measurement and prevention of construction

61 waste, regarding sustainability requirements stated by Dutch environmental policies.

2. Researches and studies mostly concerned with the economic impacts of waste in the construction industry. For example: a) The most extensive studies on this theme was carried out by Skoyles in UK year 1976 whereby he actually monitored material wastes in 114 building sites, and concluded that there was a considerable amount of waste that can be avoided by adopting relatively simple prevention procedures. Some other findings from Skoyles’s researches also pointed out that storage and handling was a major cause of waste while most of the problems concerning waste on building sites are related to flaws in the management system, and have very little to do with the lack of qualification of workers.

Besides that, Formosa and his co-authors have also documented some extensive studies and surveys done in Brazil, which the concentration of those studies were more towards identifying the types of material wastes in construction. For example,

1. Pinto developed a study in 1989 based on one site only; pointing out for the fact that indirect waste (materials unnecessarily incorporated in the building) can be higher than direct waste (rubbish that should be disposed in other areas). 2. The first research project on construction waste developed at the Federal University of Rio Grande do Sul (UFRGS) started in April 1992. The main

62 objective of that study was to analyse the main causes of material waste in the building industry in order to propose guidelines for controlling it in small sized firms. Seven building materials were monitored in five different sites during a period ranging from five to six months. 3. The Brazilian Institute for Technology and Quality in Construction (ITQC) more recently coordinated a much more ambitious research project on material waste measurement, which was developed for the Brazilian construction industry, involving 15 universities (including UFRGS) and more than one hundred building sites. For over 2 years, eighteen materials had their waste monitored by using a data collection method similar to the projects carried out at the Federal University of Rio Grande do Sul (UFRGS) in 1992.

Some conclusions that were drawn from those conventional construction waste studies above such as:

1. The waste of building materials is occasionally far higher than the nominal figures assumed by the companies in their cost estimates. 2. There is a very high variability of waste indices from site to site. Furthermore, similar sites might present different levels of wastes for the same material. This indicates that a considerable portion of this wastage can be avoided. 3. Some companies do not seem to be concerned about material waste, since they do not apply relatively simple procedures to avoid waste on site. None of them

63 had a well-defined material management policy, neither a systematic control of material usage. 4. The lack of knowledge was an important cause of waste. Most building firms did not know the amount of waste they had. 5. Most causes of waste are related to flaws in the management system, and have very little to do with the lack of qualification and motivation of workers. Also, waste is usually the result of a combination of factors, rather than originated by an isolated incident. 6. A significant portion of waste is caused by problems, which occur in stages that precede production, such as inadequate design, lack of planning, flaws in the material supply system, etc.

From here, if we take a look at a different perspective, all the above construction waste researches carried out would suggest that the flow aspects in construction have been historically neglected while previous researches were mainly concentrated on the conversion aspects in construction. If this assumption were true, it logically follows that current construction would demonstrate a significant amount of waste, loss of value, and non value-adding activities apart from the waste and value loss to the value-adding activities.

64 4.3 Waste and value loss in construction

In search for the waste, loss of value and non value-adding activities in current construction practices, Koskela (1992) has managed to present a few evidences from various partial studies done by other researchers around the world apart from the material waste from conversion activities. Although in his research paper entitled “The Application of The New Production Philosophy to Construction” stated that there has never been any systematic attempt to observe all wastes in a construction process but nevertheless, partial studies can be used from various countries to indicate the order of magnitude of non value-adding activities in construction. Basically, In Koksela’s research paper, he has been looking for the evidences of waste and value loss due to quality

of

works,

material

management,

non-productive

time,

safety

and

constructability.

4.3.1. Waste and value loss due to quality of works

The first element of waste and value loss was compiled in term of quality costs the subsequent findings from 3 different projects are stated as follow:

1. In numerous studies from different countries done in 1991, the cost of poor quality (no- conformance) as measured on site has turned out to be 10 - 20% of total project costs. In a Belgian study, it has also recorded the causes of these

65 quality problems are 46% design-related, 22% construction-related and 15% are related to material supply 2. In a very detailed Swedish study on a design-construct project carried out in 1991, the costs of quality failures for a construction company were found to be 6%. In Sweden and Germany, it was found out that external quality costs or the loss of value (understood as exceptional maintenance) to owners during facility use are estimated to be 3% of the value of annual construction production. In the case of Sweden. 51% of these costs are associated with design problems, 36% with construction problems and 9% with use problems. 3. In an American study of several industrial projects, deviation costs averaged 12.4% of the total installed project cost. The researchers of the study also recorded the causes of these quality problems are 78% design-related, 17% construction-related and 20% are related to material supply

4.3.2. Waste and value loss due to constructability

The second factor that contributed to waste and value loss as compiled by Koskela is the factor of constructability. Constructability is the capability of a design to be constructed, or in a more elaborated word, constructability of a design depends on the consideration of construction constraints and possibilities. It was found from a constructability report in 1986 stated that projects where constructability has been specifically addressed have reported 6 - 10% savings of construction costs.

66

4.3.3. Waste and value loss due to material management

Materials management in construction site was generally being neglected. Some researchers such as Bell & Stukhart have estimated that 10 - 12% savings in labour costs could be produced by materials-management systems. Furthermore, a reduction of the bulk material surplus from 5 - 10% to 1 - 3% would result from a better material management practice. Besides that, some researchers also reported that savings of 10% in materials costs can be achieved from vendor cooperation in streamlining the material flow.

4.3.4. Waste and value loss due to non-productive time

As for work flow processes, It has been found that construction work flow consists of a lot of non value-adding activities where they consume a high percentage of overall working time. All the estimation given from the researches compiled by Koskela, the average distribution of working time used in value-adding activities ranging around 30% to 40%. Oglesby and his co-author estimated around 36% in 1989 while Levy in 1991 claimed that the average share of working time is 31.9 % in the United States. There are similar figures from other countries but some other researches did show a greater variance in percentage. For example, the average distribution of working time of the 17 observed building projects survey in Chile conducted by Serpell, et al. (1995)

67 during 1990 and 1994 shows that the minimum value of productive work was 35% and the maximum was 55%.

4.3.5. Waste and value loss due to safety issues

Another waste factor is lack of safety. In the United States, safety-related costs are estimated to be 6 percent of total project costs as reported by Levitt & Samelson in 1988.

Thus, there is strong empirical evidence showing that a considerable amount of waste and loss of value exists in construction apart from the conventional understanding of physical waste or material waste. A large part of these wastes has been hidden, and it has not been perceived as actionable.

4.4 New concept of waste in production activities

In new production philosophy, “waste” has been given a broader concept and definition as compared to its usual narrow meaning. According to the new production philosophy, waste should be understood as any inefficiency that results in the use of equipment, materials, labour, or capital in larger quantities than those considered as necessary in the production of a building. Waste includes both the incidence of material losses and the execution of unnecessary work, which generate additional costs but do not add value to the product (Koskela 1992). Therefore, waste should be defined as any losses produced

68 by activities that generate direct or indirect costs but do not add any value to the product from the point of view of the client.

Two other definitions below as quoted by Alarcon (1995) expressed the broaden dimension of wastes as seen by new production paradigm.

Toyota defines waste as:

“Anything that is different from the minimum quantity of equipment, material, parts and labour time that is absolutely essential for production.”

A western definition for waste would be following:

“Anything different from the absolute minimum amount of resources of materials, equipment, and manpower necessary to add value to the product.”

In this lean production paradigm, the concept of waste is directly associated with the use of resources that do not add value to the final product. This is very much different from the conventional conversion view of production processes where not significant attempts to separate the activities into value-adding or non value-adding activities. The conventional view sees all activities combined as a whole and therefore waste is being

69 monitored and evaluated as a whole conglomerated additional costs to the production and mainly it only captured costs for the material wastes. The new production philosophy intend to look into and detail out the dimension of waste by identifying non value-adding activities and introduce new measures to wastes such as additional costs or opportunity costs especially due to time waste and value loss which very much invisible in conversion model.

Figure 4.1 will show a clearer picture on the different in concept of waste for conventional conversion model compared to new production philosophy.

Conventional View

New Production Philosophy

Total Cost of A Process

Cost of non valueadding activities

Cost of value-adding activities

Performance improvement rationale:

Increase process efficiency

Reduce or eliminate non valueadding activities and increase process efficiency of valueadding activities

Figure 4.1 Performance improvement in conventional, quality and new production philosophy approaches. (Simplified from the figure of Koskela (1992))

70 This means that there are 2 approaches to improving processes for new production philosophy compared to conventional conversion view. One is to improve the efficiency of both value-adding and non value-adding work, and the other is to eliminate waste by removing non value-adding activities. Therefore, waste should be defined as any losses produced by activities that generate direct or indirect costs but do not add any value to the product from the point of view of the client.

The ideal outcomes that can be pictured by adopting new production philosophy or lean production will be production will be managed in the way that actions are aligned to produce unique value for the client. Project duration and cost are considered in “projectas-production system” terms making concern for project total cost and duration more important than the cost or duration of any activity. Coordination is accomplished in general by the central schedule while the details of work flow are managed throughout the organisation by people who are aware of and support project goals performance. The primary objectives for this new movement will be looking at value to the client and throughput, the movement of information or materials to completion. Improvement results from reducing waste that is the difference between the current situation and perfection, i.e., meeting customer unique requirements in zero time with nothing in store.

71 4.5 Underlying the waste concepts in construction

In construction, the application of the lean production model mainly stems from a discussion of Koskela's work, which emphasised the importance of the production process flow, as well as aspects related to converting inputs into finished products as an important element to reduce wasted value. Production should be seen as a flow that generates value through conversion processes, characterised by cost, time frame, and the degree of added value. In other word, the new production theory seeks cycle time reduction, total waste elimination, zero defects and flexible output and in doing that, it requires the evaluation of new measurements, such as waste, value, cycle time or variability that was not covered under traditional concepts.

It is worthwhile to understand the construction production process before underlying the waste concepts in construction. Koskela (1992) has proposed a flow process model, in which production is conceived as a flow of materials and information through four types of stages: transport (moving), waiting (delay), processing (conversion), and inspection as shown in Figure 2. This model differentiates between value-adding activities and non value-adding activities and also concentrates on the process flow rather than the exchange among the processes. As a rule in this model, only processing activities are value-adding activities. Reducing the share of the non value-adding activities is the target for continuous improvement. (Koskela, 1992)

72

REJECT MOVING

WAITING

INSPECTION

PROCESSING A

REWORK

REWORK MOVING

WAITING

PROCESSING B

INSPECTION

REJECT

Figure 4.2 Koskela’s flow process model (Koskela 1992)

Serpell et al. (1995) have proposed a much more open and dynamic construction process model as described in Figure 4.3. The model presents the construction production process on which work has been based on a system that correlated with the environment around it. Part of the environment is controllable but other factors are outside of its control.

Figure 4.3 Serpell’s Modeling of the construction process (Serpell et al. 1995)

73

The main and most critical components of the construction process as portrayed in Figure 4.3, are:

1. Flows and conversion management: Responsible of making the decision that define the performance of the system 2. Flows: Are the inputs to the system and they contemplate all activities up until the completion of the end product. Those inputs can be separated in two types, resources (labour, materials and construction equipment), and information. There are two types of flows as portrayed in the model: external flows and internal flows. External flows are usually uncontrollable such as Suppliers’ provision of resources and design information. Internal flows are usually controllable such as flows of materials from a warehouse. 3. Conversion activities: The processes that transform the flows into finished and semi-finished products. The method used in this activities decided by the flows and conversion management. 4. Products: The results of conversion activities.

There are three areas or elements of interest where waste can occur and improvements can be carried out according to Serpell’s model:

74 1. Flows, both internal and external, which are the inputs to the conversion activities and can be classified into two groups: construction resources (materials, labour and equipment) and construction information. 2. Conversion processes and resultant products, which are the processes that transform the flows into completed and partially completed products. 3. Flows and process management which corresponds to the management actions and decisions that determine the way things are done and the application of construction resources. This management is responsible for the performance of the construction process and is characterised by different styles or approaches according to companies and managers.

Waste elimination/ reduction (alongside value enhancement to construction), still remained prominent focus in the current lean construction practices for process improvement. This is because from experience shows those non value-adding activities, which involved human in the flow of work, predominate in the majority of processes. Taylor (1913) pointed out that the economic loss caused by material waste is smaller than the ones related to the inefficiency of human work. Ford (1927) also suggested that human work should be the focus of waste prevention, since the value of materials depends, to a great extent, on the work that has been spent on them. Studies had shown that usually around 3% to 20% of the steps add value, and their share in total cycle time is only around 0.5% to 5% (Alarcon, 1994).

75 4.6 Waste classification

Industry researchers and practitioners have acknowledged that there are many non-value adding activities during the design and construction process and majority of those wasteful activities consuming time and effort without adding value for the client. Since the beginning of a construction project, Construction Managers have to deal with many factors that may negatively affect the construction process, producing different types of waste (Serpell et al, 1995). Waste includes both the incidence of material losses and the execution of unnecessary work that generates additional costs but does not add value to the product (Koskela, 1992). Moreover, some researchers, Alarcon (1993), Koskela (1992) and Serpell et al. (1995) stated that waste in construction and manufacturing include delay times, quality costs, lack of safety, rework, unnecessary transportation trips, long distances, improper choice of management, methods or equipment and poor constructability.

Regarding the possibility to control the incidence of waste, Formoso, et al. (1999) commented that there is an acceptable level of waste, which can only be reduced through a significant change in the level of technological development. Based on the ratio of prevention investment cost over the cost of waste itself, they have classified wastes into two general groups:

1. Unavoidable waste (or natural waste), in which the investment necessary to its reduction is higher than the economy produced, The percentage of unavoidable

76 waste in each process depends on the company and on the particular site, since it is related to the level of technological development.

2. Avoidable waste, when the cost of waste is significantly higher than the cost to prevent it.

Waste can also be classified according to its origin, i.e. the stage that the main root cause is related to. Although waste is usually identified during the production stage, it can be originated by processes that precede production, such as materials manufacturing, training of human resources, design, materials supply, and planning. However, the most classical waste classification according to lean production paradigm is perhaps the classification done by Shigeo Shingo in his book “Study of Toyota Manufacturing System” in 1981 as it has been quoted by various other lean construction researches in relation of the study of wastes in construction example Alarcon (1994), Womack and Jones, (1996), Formoso, et al. (1999), Koskela (2000) and many others.

Shingo proposed the following waste classification whereby waste was classified by it nature, which based on the Ohno’s framework of Toyota Production System:

1. Waste due to overproduction; 2. Waste due to wait periods; 3. Waste due to transport;

77 4. Waste due to system itself; 5. Waste due to stock; 6. Waste due to operation; 7. Waste due to defects;

Based on Shingo’s seven wastes, Formoso, et al. (1999) went on to propose their main classification of waste based on the analysis of some Brazilian building sites they had carried out as shown below. It was thought that the further classification will help managers to understand the different forms of waste, why they occur and how to act in order to avoid them.

1. Overproduction: related to the production of a quantity greater than required or earlier than necessary. This may cause waste of materials, man-hours or equipment usage. It usually produces inventories of unfinished products or even their total loss, in the case of materials that can deteriorate. An example of this kind of waste is the overproduction of mortar that cannot be used on time.

2. Substitution: is monetary waste caused by the substitution of a material by a more expensive one (with an unnecessary better performance); the execution of simple tasks by an over-qualified worker; or the use of highly sophisticated equipment where a much simpler one would be enough.

78 3. Waiting time: related to the idle time caused by lack of synchronisation and levelling of material flows, and pace of work by different groups or equipments. One example is the idle time caused by the lack of material or by lack of work place available for a gang.

4. Transportation: concerned with the internal movement of materials on site. Excessive handling, the use of inadequate equipment or bad conditions of pathways can cause this kind of waste. It is usually related to poor layout, and the lack of planning of material flows. Its main consequneces are: waste of man hours, waste of energy, waste of space on site, and the possibility of material waste during transportation.

5. Processing: related to the nature of the processing (conversion) activity, which could only be avoided by changing the construction technology. For instance, a percentage of mortar is usually wasted when a ceiling is being plastered.

6. Inventories: related to excessive or unnecessary inventories which lead to material waste (by deterioration, losses due to inadequate stock conditions on site, robbery, vandalism), and monetary losses due to the capital that is tied up. It might be a result of lack of resource planning or uncertainty on the estimation of quantities.

79 7. Movement: concerned with unnecessary or inefficient movements made by workers during their job. This might be caused by inadequate equipment, ineffective work methods, or poor arrangement of the working place.

8. Production of defective products: it occurs when the final or intermediate product does not fit the quality specifications. This may lead to rework or to the incorporation of unnecessary materials to the building (indirect waste), such as the excessive thickness of plastering. It can be caused by a wide range of reasons: poor design and specification, lack of planning and control, poor qualification of the team work, lack of integration between design and production, etc.

9. Others: waste of any nature different from the previous ones, such as burglary, vandalism, inclement weather, accidents, etc.

Some researchers have proposed some qualitative model by postulating the loss of productivity in construction using categories of non-productive time. Researchers such as Borcherding in 1986 explained the loss of productivity in large and complex constructions using five categories of non-productivities time as listed below:

1. Waste due to waiting or idle; 2. Waste due to travelling; 3. Waste due to slow work;

80 4. Waste due to ineffective work; 5. Waste due to rework

Borcherding’s five waste categories of non-productive time are found very much similar to the categories of wastes of productive time proposed by Serpell et. al (1995) derived from their case studies as shown Figure 4.4 below: Waiting time Work inactivity

Idle time Travelling Resting

Waste of time (man-hours & equipment time)

Physiological needs

Reworking Ineffective work

Working slowly Inventing work

Figure 4.4 Categories of wastes of productive time (Serpell et al. 1995)

However, they highlighted some limitations to the waste classification of nonproductive time for example the waste of time related to slow work is related to the efficiency of processes, construction equipment and personnel. But it is difficult to measure it because it is first necessary to know the optimal efficiency that can be achieved, which is not always possible.

81 Instead of classifying the waste of productive time, Serpell et. al (1995) went a step further to breakdown those wastes factors in relation of work categories. There are 3 types of work categories as proposed:

1. Productive work (value-adding activities) 2. Contributory work (non value-adding activities but essential for conversion process): Those contributory work which are classified as waste include transporting, instruction, measuring, cleaning and others 3. Non-contributory work (non value-adding activities): Those non contributory work which are classified as waste include waiting, idle time, travelling, resting, physiological needs, and rework

There are also other categories of waste that have been mentioned in the literature, such as accidents, working under sub-optimal conditions (Koskela 2000), design and products that do not meet users’ needs. (Womack and Jones 1996) The main role of existing classification of waste is to call the attention of people to most likely problems, since not all waste is obvious: it “often appears in the guise of useful work.” (Shingo 1988)

4.7 Key construction waste causes

After understanding the classification of waste, it is important to examine the type of possible causes that lead to the occurrence of waste in construction process. This is

82 deem important because just by knowing the waste itself just would help to monitor them but not reduce or eliminate them from the process loops.

To work out a

continuous improvement strategy in reducing and eliminating those wastes in construction processes, the origin of the waste itself has to be identified.

A typical waste identification survey underlined a few examples of waste sources according to different area of functions such as administration, use of resources and information systems. Several potential sources of waste can be grouped under the particular area of functions and it can be created to suit the need of particular projects such as the diagnostic survey developed by students Francisco Lowener, Francisco Lira and Marcelo Beratto as documented by Alarcon (1994) listed down the following potential sources of waste in their project:

A. Administration 1. Unnecessary requirements 2. Excessive control 3. Lack of control 4. Poor planning 5. Bureaucracy B. Use of resources 1. Surplus 2. Shortage 3. Misuse

83 4. Poor distribution 5. Poor quality 6. Availability C. Information systems 1. Unnecessary 2. Defective 3. Late 4. Unclear

Serpell et. al (1995) on the other hand identified several controllable causes of waste. Although his study was mainly concentrated on wasted time but the classification of the causes to waste is found rather structured and detailed compared to the previous listed in waste identification survey. They divided the controllable wastes as identified from their research projects into three different activities, which associate to flows, conversions, and management activities.

1. Controllable causes associated to flows The principal flow causes were as follow: a) Resources q

Materials: Lack of materials at the work place; materials are not well distributed; inadequate transportation means

q

Equipment:

Non

availability;

equipment for work needs

inefficient

utilisation;

inadequate

84 q

Labour: personal attitudes of workers; stoppage of work

b) Information q

Lack of information;

q

Poor information quality

q

Timing of delivery is inadequate

2. Controllable causes associated to conversions The following causes were identified: a) Method q

Deficient design of work crews

q

Inadequate procedures

q

Inadequate support to work activities

b) Planning q

Lack of work space

q

Too much people working in reduced space

q

Poor work conditions

c) Quality q

Poor execution of work

q

Damages to work already finished

3. Controllable causes associated to management activities The following causes were identified: a) Decision making q

Poor allocation of work to labour

q

Poor distribution of personnel

85 b) Ineffective supervision/ control q

Poor or lack of supervision

4.8 Modeling waste and performance in construction

Modelling and evaluation of wastes and performance in construction projects has been a challenge for the construction industry for decades. Several models and procedures have been proposed for the evaluation of project performance at site and project level. Some of these models focus on prediction of project performance while others focus on measuring. Traditional models offer only a limited set of measures as most of them limit their analysis to a number of measures such as cost, schedule, or productivity (usually labour productivity).

The introduction of new production philosophies in construction requires new measures of performance (Koskela, 1992), such as waste, value, cycle time or variability. The shortcomings of the traditional control systems, and models are unable or not appropriate to measure those new performance elements but Alarcon (1993) suggested that some of the concepts developed in previous research can be utilised in modelling new performance elements for construction required for continuos improvement.

It is worthwhile to point out some of opinions of different researchers and authors related to the extent of performance elements in the aspects of construction process. Among all, one of the most classical opinions was from Sink (1985, as documented by

86 Alarcon 1993). Sink has characterised performance in a broad definition, as 7 criteria or elements on which management should focus its efforts on: Those 7 criteria or elements are as explained below:

1. Effectiveness: A measure of accomplishment of the ‘right’ things: a) On time (timeliness), b) Right (quality), c) All the ‘right’ things (quantity), where ‘things’ are goals, objectives, activities and so forth, 2. Efficiency: A measure of utilization of resources. It can be represented as a ratio of resource expected to be consumed divided by the resources actually consumed 3. Quality: A measure of conformance to specifications. In construction projects, quality has 2 dimensions: a) The first and overall one is that of the completed project functioning as the owner intended b) The second concerns the many details involved in producing the results 4. Productivity: Theoretically this is defined as a ratio between output and input and it is primary measured in terms of cost. In the context of the construction industry, the output is the structure or facility that is built or some components of it. The major input into the construction process includes work force, materials, equipment, management, energy and capital.

87 5. Quality of work life: A measure of employees’ affective response to working and living in organizational systems. Often, the management focus is on insuring that employees are ‘satisfied’, safe and secure and so forth 6. Innovation: This is the creative process of adaptation of product, service, process or structure in response to internal as well as external pressures, demands and changes, needs and so forth 7. Profitability: A measure or a set of measures of the relationships between financial resources and uses for those financial resources. For example, revenues/ costs, return on assets and return on investments.

Embarking with the new production philosophies, Koskela (1992) has proposed some new measures as required for construction, to stimulate continuous improvement such as: 1. Waste: Number of defects, rework, number of design errors and omissions, number of change orders, safety costs, excess consumption of materials, etc; 2. Value: Value of the output to the internal customer; 3. Cycle time: Cycle time of main processes and sub processes; 4.

Variability: Deviations from the target, such as schedule performance.

The problem of performance evaluation is a multi-attribute or multi-criteria one. Generally, the evaluations of performance in construction are concentrated on few aspects only mainly on profitability and productivity. Furthermore, different managers probably will use different performance elements and some will have different weight

88 for each individual measures. Therefore, a model for evaluation or prediction must have the flexibility to include the individual organisational objectives in the evaluation process. It also must have the ability to examine the effect of changes in those objectives in the evaluation process.

There are a few categories of performance and evaluation models, which can be grouped by the functions of each model as discussed in Luis F. Alarcon (1993) in his paper entitled “ Modeling waste and performance in construction”.

1. Measurement and Performance Evaluation Models Function: Establish a framework for measurement and evaluation that may allow improved quality of the information available for decision-making and research. Examples: a) Delay models use stopwatch techniques to record productive time and delay occurring during the day b) Work study-based models which are extensively used to indirectly measure labour productivity c) Activity models use work sampling techniques to catagorise activities observed into productive, supportive or idle times.

2. Prediction Models Function: Provide systematic procedures to account for the different factors that affect productivity

89

3. The Productivity Theory Factors Model Function: Provides both standard procedures for collecting information and a more rigorous way of accounting for productivity factors.

4. The Conceptual Construction Process Model Function: Shows a different perspective on the problem that explains more thoroughly the functional relationships and influences that affect productivity

5. Casual Models Function: Provide a qualitative model structure to explore actions that can affect productivity and to understand the mechanisms which product the results.

It is important to build a bridge between traditional and new philosophies in construction performance improvement. As suggested by Alarcon (1993) that traditional models and concepts in measuring and evaluating performance elements can be improvised in order to incorporated new performance elements proposed by new production philosophies.

90 CHAPTER 5

RESEARCH METHODOLOGY

5.1 Introduction

This chapter will explain the methodology in carrying out this academic research. Aspects involved included method of research, research subjects, tools for analysis, points or marks assignment, sequences of research, and analysis of the research data.

5.2 Method of research

The purposes of this research are to see whether the lean construction principles of waste concepts have been well comprehended, accepted and adopted by the local construction personnel especially in waste recognition, reduction and elimination for the continuous improvement in construction processes. A quantitative research approach was adopted for this research requiring the development and dissemination of a questionnaire survey. Due to the population of this research are virtually too difficult to be quantified as the main targeted respondents would include all personnel who has direct managerial experiences in construction field, the non-probability sampling methods will be adopted in this research instead of probability sampling. Purposive sampling for specific groups or types of respondents will be conducted by using expert sampling technique which involves the assembling of a sample of managerial personnel with known or demonstrable experience and expertise in managing construction field

91 processes. The expert sampling has been seen as the best way to elicit the views of those who have specific expertise and experiences dealing with the local construction practices. It is also very useful for situations where a targeted sample needs to be reach quickly and where sampling for proportionality is not the primary concern in this research.

The research is conducted through structured questionnaires where those questionnaires were sent to the particular “qualified” respondents. The respondents were approached through their companies and firms, which registered in the CIDB annual directory yearbook. A pilot survey was conducted during November year 2003 where 20 sets of questionnaires were sent out to a random group of pilot respondents in postal mail (with returned envelop and stamp attached) around peninsular Malaysia for a period of 1 month but the respond rate to the questionnaires were are low with only 2 sets of surveys were returned during the trial period.

Due to the circumstances of low respond rate in the pilot survey, a new approach of distributing the questionnaires has been taken. The targeted research locations have been focus more into northern region of peninsular Malaysia where direct contacts with the potential qualified respondents were more easily accessible. Besides 20 new sets of questionnaires were posted out together with 20 sets post out through e-mail throughout peninsular Malaysia, there were also 30 sets of questionnaires were hand-delivered (mainly in northern Peninsular Malaysia) to the respondents from December 2003 until February 2004. Until the due date, 27 of questionnaires were returned (including 2 from pilot survey) which represented an average response rate of 30%. Compared to the 40%

92 average response rate for the 5 years quantitative research carried out by Alwi et al (2002) on construction wastes in Indonesia with 300 questionnaires sent, this research carried out are considerably low in average response rate but if compared to the timeframe and resources available for data collection in this research, the 30% response rate are reasonably acceptable for numbers of questionnaires sent.

This research was postulated around determining the general perceptions and actions of the construction personnel against wastes in construction and the concept of nonproductive time or wasted time as suggested by Serpell et al. (1995) were then integrated into the research process as the key element of lean construction philosophy regarding flow concept. In this case, Waste in construction process is classified into three main categories, which are direct conversion waste, non-contributory time waste and contributory time waste. 19 waste elements are outlined consists of 9 direct conversion wastes, 7 non-contributory time wastes and 3 contributory time wastes as shown in Table 5.1 and all those waste elements were derived from different previous studies carried out by Serpell et al (1995), Alarcon (1994 & 1995), Formosa, et al (1999 & 2002) and Alwi et al (2002).

93

Direct Conversion Wastes

Non-Contributory Wastes

Contributory Wastes

1

Over-allocation/ unnecessary equipment on site

Time in supervising and inspecting the construction works

2

Over-allocation/ unnecessary materials on site

Waiting for others to complete their works before the proceeding works can be carried out (idle time) Waiting for equipment to be delivered on site

3

Over-allocation/ unnecessary workers on site Unnecessary procedures and working protocols Material loss/ stolen from site during construction periods

4 5

6

7

8 9

Material deterioration/ damaged during construction periods Mishandling or error in construction applications/ installation

Waiting for materials to be delivered on site Waiting for the skilled workers to be on site Waiting for the clarification and confirmation by client and consultants Time for rework/ repair works/ defective works (Rework) Time for workers’ resting during construction (Physiological needs & Resting)

Time for instructions and communication among different tiers and trades of workers Time for transporting workers, equipment and materials

Materials for rework/ repair works/ defective works Accidents on site

Table 5.1 Waste elements in 3 separate waste groups

In response to the examine the frequencies causes of wastes and their inter-relation with waste elements, several waste causes factors were also substrated from previous literature studies by Serpell et al (1995), Alarcon (1994 & 1995) and Alwi et al (2002) and categorised into 5 main groups of cause factors which are Management & Administration Factors (4 factors), People Factors (6 factors), Execution Factors (6 factors), Material Factors (6 factors) and Information and Communication Factors (3 factors). The entire breakdown of the waste cause factors is shown in Table 5.2.

94

Management & Administration Factors Poor coordination among project participants 1 Poor planning and scheduling 2 Lack of control 3 Bureaucracy 4 People Factors Lack of trades skills 1 Inexperience inspectors 2 Too few supervisors/ foreman 3 Uncontrolled sub-contracting practices 4 Supervision too late 5 Poor labour distribution 6 Execution Factors Inappropriate construction methods 1 Outdated equipment 2 Equipment shortage 3 Poor equipment choice or ineffective equipment 4 Poor site layout and setting out 5 Poor site documentation 6 Material Factors Delay of material delivery 1 Poorly scheduled delivery of material to site 2 Poor quality of material 3 Inappropriate/ misuse of material 4 Poor storage of material 5 Poor material handling on site 6 Information and Communication Factors Defective or Wrong information 1 Late information and decision making 2 Unclear information 3

Table 5.2 Waste Causes Factor Group

95 5.3 Profile of respondents

A randomly selected group of targeted respondents consists of those personnel who have a commanding role in the construction process and resource management and extensive site experiences were targeted as respondents for the sample survey. There has been a wide spectrum of personnel with different position and job title, which had been responded to the survey and for the purpose of analysis and comparison, the whole sample of respondents have been regrouped into 2 main categories which are 1. Project management orientated group 2. Site operative management orientated group

Project management orientated group will feature those who have relatively more responsibilities in overall project execution and resource management and not so much on site operative management by its nature of job scope. Therefore, this group will involve personnel more on planning, inter-coordinating and directing role in construction process and as for the sample respondents for this research will include project managers, general managers, project schedulers/ planners, quantity surveyors.

While Site operative management orientated group will feature those who have relatively more responsibilities on the site operative management by its nature of job scope. The group will mainly involve personnel in solving construction problems on site, more on intra-coordinating with internal groups and trades, and as for the sample

96 respondents for this research will include site managers, site engineers, resident architect/ engineer and senior quality manager.

5.4 Structure of questionnaires

The structure of questionnaires is divided into 5 main sections. (Refer sample of questionnaire in Appendix 5) The first 2 sections of questionnaires are intended to examine the general perception and acceptance of Lean Construction philosophy of local construction industries based on the respondents’ waste concepts. In this case, the respondents were asked to recognise 19 wastes elements and their personnel experiences in controlling those waste elements during construction processes. There are 2-options available for the respondents and there were required to answer whether the wastes elements as listed is a waste or non-waste and whether they are controlled or not controlled during the construction processes.

The third and fourth sections are intended to review the extent of waste problems in existing local industry by ranking them in term of frequencies of occurrences and rate the likelihood of particular waste sources/ causes in their construction practices where they work. For section 3, Respondents were able to identify how frequently the waste occurred using 5 categories: (1) Never; (2) Very Rare; (3) Seldom; (4) Frequent; and (5) Very Frequent and the respondents were provided with five different scales from 1 (no significant effect variable) to 5 as (high detrimental effect variable); Foe section 4, Respondents were asked to determine the likelihood of particular waste sources/ causes

97 using 4 categories: (1) Most unlikely; (2) Unlikely; (3) Likely; (4) Most Likely and the respondents were provided with five different scales from 1 (no significant likelihood) to 5 as (high detrimental likelihood)

The fifth section is to examine the relevant sources of wastes as outlined in the fourth section to have caused the particular construction wastes. The respondents were asked to identify the most possible causes and other possible causes to the wastes elements in order to create a matrix table between construction wastes and their sources of wastes.

5.5 Score Assignment

Score assignment is a process of assigning values for each of the item and this is an important process of conducting inferential analysis especially for correlation test using Pearson-r where aggregation of points are required for this research. Score assignment for section 1 and 2, each positive answer is assigned with 2 points and each negative answer is assigned with 1 point. Based on the waste categories in Table 5.1, the maximum points for direct conversion wastes that can be aggregated for each case is (2 X 9) equal to 18 points and the minimum of (1 X 9) equal to 9 points; Maximum points for non-contributory time waste is (2 X 7) or 14 points and minimum of (1 X 7) or 7 points whereas for maximum points for contributory time wastes is (2 X 3) or 6 points and minimum of (1 X 3) or 3 points

Score assignment for section 3 and 4 is based on the multiple-scale format. For section 3, points are ranged from 1 to 5 and maximum points that can be aggregated for direct

98 conversion wastes is (5 X 9) or 45 points, minimum of (1 X 9) or 9 points; for noncontributory time wastes, maximum that can be achieved is (5 X 7) or 35 points and minimum of (1 X 7) or 7 points while maximum for contributory time wastes is (5 X 3) or 15 points and minimum of (1 X 3) or 3 points. For section 4, points are ranged from 1 to 4 but since correlation are not going to be tested in this section but rather each item is going to be tested separately with One-way t-test for ranking purposes, therefore not aggregation of points are required.

5.6 Analysis Methods

After all the primary data have been collected and processed, those data will then be analysed according to the appropriate analysis methods. Analysis methods in this research are mainly divided into 2 parts: (1) Descriptive analysis and (2) Inferential statistical analysis. Descriptive statistical analysis is used to present the background profiles about the respondents and provide further information for the inferential statistical analysis, besides that, the analysis on the descriptive data about the waste recognition and waste control events in section 1 & 2 will also be conducted under the same category. Inferential statistical analysis will be used to test certain research hypothesis, type of analysis tools to be used include Coefficient Pearson r for correlation testing and one-way t-test for frequencies ranking.

In most analyses carried out in 3 separate categories namely direct conversion wastes, contributory process time wastes and non-contributory process time wastes in order to

99 see the different between each categories especially dealing with contributory process wastes and non contributory process waste which is rarely considered in conventional waste concepts for construction processes.

Although it is logically understood that when we recognised certain wastes, we will try our best to avoid it or control it, however, in this research, the inter-relationship between understanding of wastes and actual control practices of wastes in construction processes will be examined in order to found out any contradictions to the logic of relationship between recognising the waste and the actions in controlling them. 4 different scenarios are anticipated which are extreme scenarios where type of waste elements are recognised as waste and have been given a proper attention in controlling them or vice versa not recognising them and therefore not given any control actions into it. Of course, another 2 scenarios the cases would be the potential cases of recognising the waste elements but do not act on them or vice verse acting on certain waste elements which they are not recognised as waste.

On the other hand, Inferential statistic analysis will use correlation Pearson-r to conduct testing on 9 hypotheses to see whether any significant inter-relationship existed between understanding of wastes and actual control practices of wastes in construction processes based on 3 cases of waste categories. The 9 hypotheses are:

Hypothesis 1: There is inter-relationship between construction’s direct conversion wastes are been perceived with the tendency to control those wastes

100 Hypothesis 2: There is inter-relationship between construction’s direct conversion wastes are been perceived with the frequencies of occurrences of such wastes during the processes Hypothesis 3: There is inter-relationship between the tendency to control those construction’s direct conversion wastes with the frequencies of occurrences of such wastes during the processes Hypothesis 4: There is inter-relationship between construction’s non-contributory time wastes are been perceived with the tendency to control those wastes Hypothesis 5: There is inter-relationship between construction’s non-contributory time wastes are been perceived with the frequencies of occurrences of such wastes during the processes Hypothesis 6: There is inter-relationship between the tendency to control those construction’s non-contributory time wastes with the frequencies of occurrences of such wastes during the processes Hypothesis 7: There is inter-relationship between construction’s contributory time wastes are been perceived with the tendency to control those wastes Hypothesis 8: There is inter-relationship between construction’s contributory time wastes are been perceived with the frequencies of occurrences of such wastes during the processes Hypothesis 9: There is inter-relationship between the tendency to control those construction’s contributory time wastes with the frequencies of occurrences of such wastes during the processes

101 In every case above, the correlation Pearson-r will tell us the magnitude and direction of the association between two variables. SPSS creates a correlation matrix of the two variables. All the information we need is in the cell that represents the intersection of the two variables. In SPSS, the outcomes of the Pearson-r analysis will provide us three pieces of information: (1) the correlation coefficient, (2) the significance and (3) the number of cases (N) The correlation coefficient is a number between +1 and -1. This number tells us about the magnitude and direction of the association between two variables. The magnitude is the strength of the correlation. The closer the correlation is to either +1 or -1, the stronger the correlation. If the correlation is 0 or very close to zero, there is no association between the two variables. The direction of the correlation tells us how the two variables are related. If the correlation is positive, the two variables have a positive relationship (as one increases, the other also increases). If the correlation is negative, the two variables have a negative relationship (as one increases, the other decreases).

One-Way t-test will be carried out basically to get the ranking on the frequencies of occurrence of the wastes elements in section 3 and the likelihood of recognition certain wastes causes factors as in section 4. In SPSS, the outcomes of the One-Way t-test analysis will provide us four pieces of information: (1) the number of cases (N), (2) the mean value, (3) the standard deviation and (4) the standard error means. The ranking will be done separately in a descending order from the greatest magnitude of the mean

102 value to the lowest mean value to differentiate the degree of frequencies and likelihood from the less significant to the most significant as rated by the respondent of the research. The last part of the analysis will be involving the development of the Causes and Effects Matrix table by combining all the inputs by the respondents in section 5 into the whole list of construction wastes and waste causes table. From there, descriptive statistic analysis will take place in sorting out the wastes causes factors and put them into 6 wastes factors as discussed previously and represent the Matrix Table in Bar charts format for easy interpretation of the results.

103 CHAPTER 6

DATA ANALYSIS AND INTERPRETATION

6.1 Introduction

This chapter will present all the results obtained from the data analysis waste concepts and waste causes factors in construction processes. Descriptive statistic analysis and inferential statistic analysis will be utilised to present the results. The presentation of analysis of descriptive statistic analysis will be conducted in the form of bar charts, pie charts and matrix tables to show the distribution and frequencies of the particular variables. The presentation of analysis of inferential statistic analysis will be done by using result outputs generated directly from SPSS 10.0

6.2 Descriptive analysis results

This section will discuss about the analysis results from descriptive analysis. The segments, which are in the discussion, include information about the respondents and their organisation’s background and the respondent’s waste perceptions and control actions grouped under the waste categories as outlined in Chapter 5.

104 6.2.1 Respondents and their organisation’s background

There are 5 segments analysed under this category include the position of the respondents in their organisation, nature of their work grouped as outlined in Chapter 5, main core construction projects handled by their organisation, CIDB registration grade of their firm, and their main project clients. This descriptive analysis will eventually show the actual profile of the respondents who have eventually taken this waste construction study.

105 6.2.1.1 Position of respondents

The respondents for this research consists of 27 project and site management personnel with a wide spectrum of positions ranging from project manager, project planner, general manager, quantity surveyor, resident engineer/ architect, site engineer, site manager and senior quality manager. Results from the data analysis has seen that 2 position of respondents figured almost 63% of all the other position held by the respondents in the organisation, those two positions are project manager (9 Nos) and site engineer (8 Nos). The composition of the respondent’s position are shown in the Figure 6.1 below:

9 8 7 6

Project Manager Project Planner

5

General Manager

Nos.

Quantity Surveyor 4

Site Manager Site Engineer

3

Resident Architect/ Engineer Sr. Quality Manager

2 1 0 1 Position

Figure 6.1 Composition of respondent’s position

106 6.2.1.2 Nature of work of respondents

Based on the data of the respondent’s position in their organisation, the further categorisation of their positions has to be conducted for the purposes of statistic analysis later in the chapter. The categorisation is based on the nature of work as outlined in chapter 5. 27 respondents are to be categorised into 2 main groups, which are project management orientated group and site operative management group. The results from the categorisation found that there is rather balance in term of percentage between both designated groups where each holds approximate 50% from the poll. Figure 6.2 will present the percentage of those different groups

48%

52%

Project Management Site Management

Figure 6.2 Percentage of categorisation of respondent’s nature of work

107 6.2.1.3 Main core construction projects involved by the respondent’s organisation

Respondents were asked to select the most appropriate type of construction project, which represent the main core construction projects involved by their company. The results from the data analysis show almost 78% of the records for core construction projects are made up of public & community buildings (8 Nos), residential & commercial scheme (7 Nos) and Industrial projects (6 Nos). High-rise building and civil & road construction each only recorded 3 Nos. each by the respondents as main core construction projects by their firm. Figure 6.3 shows the composition of the projects distribution:

8 7 6

Highrise Building

5

Residential & Commercial Building Industrial Building

Nos. 4 3

Public & Community Building

2

Civil & Road Construction

1 0 1 Main core construction projects

Figure 6.3 Composition of the main core construction projects by the respondent’s company

108 6.2.1.4 CIDB registration grade of the respondent’s companies

The respondents were also asked to indicate the CIDB registration grade into 2 categories that are Below Grade 3 and Grade 3 and above. The analysis results from this sample of respondents show that big portions of respondent’s companies obtain CIDB registration Grade 3 and above which are almost 83% of the total sample or (22 Nos). Only 3 companies are with CIDB registration below grade 3 only or about 11% of the overall sample while there are 2 Nos. missing input in this field. (Refer Figure 6.4)

7%

11%

82%

below Grade 3 Grade3 & Above Missing

Figure 6.4 CIDB registration of the respondent’s company

109 6.2.1.5 Main project clients

There are 2 types of main project clients classified related to the projects that their company was engaged with and the respondents are to select between private clients and public clients as their main project clients. The analysis results recorded a fair share of main project client based among this sample of respondents where 15 of the respondents reported that their main clients are from the private sectors (or about 55%) and 12 of the respondents reported their main clients are from public sectors (or about 45%). (Refer Figure 6.5)

44%

56%

Private Public

Figure 6.5 Percentages of main project clients of the respondent’s company

110 6.2.2 Respondent’s waste perceptions and control actions

The descriptive analysis on the respondent’s waste perceptions and control actions will mainly focusing on identifying the numbers of counts on wastes recognised and waste events controlled as reckon by the respondents for 3 waste categories as defined in Chapter 5 namely, direct conversion wastes, non contributory wastes and contributory wastes.

Since the lean construction philosophy considered all those waste elements as tabulated in the questionnaires as construction wastes which need to be reduced, eliminated or somehow controlled, the degree of perceptions on wastes for the local construction industries eventually can be verified by determining the numbers of positive counts on each of those wastes elements. Besides that, an analysis over a matrix tables by crosstabbing both the waste concepts and waste control actions will be carried out to study the frequencies of 4 different potential scenarios which are anticipated to be occurred.

6.2.2.1 Analysis on direct conversion wastes

Under this category, there are 9 wastes elements, which were asked to be identified by the respondents based on their own experience and opinion. Those items are indexed as F, G, H, I, J, K, L, N, S in the section A, B and C of the questionnaires. For the total of 27 respondents by calculation as (9 X 27), it sums up a total of 243 overall counts of inputs.

111 For construction waste recognition, all the inputs are tabulated in Table 6.1 below and a total of 204 positive counts are recorded or approximately 84% and it is shown a high recognition on the waste concepts for the elements tested in this category. # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

F 2 2 2 2 1 2 2 1 1 1 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2 1 1

G 2 2 2 2 1 2 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2

H 2 2 2 2 1 2 2 1 1 1 2 2 2 2 2 2 2 2 1 2 2 1 2 2 2 1 2

I 2 2 1 2 1 2 2 2 2 2 2 1 2 2 1 2 2 2 2 2 2 1 2 2 2 2 2

J 2 2 2 2 2 2 2 1 2 1 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2

K 2 2 2 2 2 2 2 1 2 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2

L 2 2 2 2 2 2 1 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

N 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

S 2 1 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 1 2 2

1 NON WASTE 2 WASTE Legend: F: Over-allocation/ Unnecessary equipment on site G: Over-allocation/ unnecessary materials on site H: Over-allocation/ unnecessary workers on site I: Unnecessary procedures and working protocols J: Material loss/ stolen from site during construction periods K: Material deterioration/ damaged during construction periods L: Mishandling or error in construction applications/ installation N: Materials for rework/ repair works/ defective works S: Accidents on site

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6. 1 Construction waste recognition under direct conversion waste category

112 This analysis concluded that a high recognition rate on direct conversion wastes by the respondents. The breakdown of numbers of the waste elements recognised as wastes under this direct conversion category are shown in Figure 6.6 below. The result shows that Item N: (Materials for rework/ repair works/ defective work) is the most recognised construction wastes with 26 positive counts while Item F: (Over-allocation/ Unnecessary equipment) is the least recognised construction wastes with only 19 positive counts under the direct conversion waste category.

30

5

25

5

3

2

4

25

23

24

1 4

7

8 20

15

22 10

22

Non Waste

26 23

Waste

20

19

5

0 F

G

H

I

J

K

L

N

S

Figure 6.6 Breakdown of direct conversion waste recognition cases

For construction waste events control, due to a respondent miss out on the whole range of input for this section, the total counts will calculated as (9 X 26) equal to 234Nos. of inputs as tabulated in Table 6.2 below. A total of 168 positive counts are recorded or

113 approximately 72% and it shows a slight drop in percentage on the waste control practices for the elements tested compared to the construction waste recognised previously by the same set of respondents. In other words, the respondents recognise the direct conversion wastes more than eventually control them.

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

F 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 2

G 2 2 2 2 1 2 2 2 2 1 2 2 1 2 2 2 1 2 2 2 2 1 1 2 2 2

H 2 2 2 2 1 2 2 2 2 1 2 2 1 2 2 2 1 2 2 2 2 1 1 2 2 2

I 2 2 2 2 2 1 2 2 1 2 1 1 1 2 2 2 2 2 2 1 2 2 1 1 2 2

J 1 1 1 1 2 1 2 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 1 1 2

K 1 1 2 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 1 1 2

L 2 2 2 2 2 1 2 2 2 1 2 1 1 2 2 2 2 2 2 2 2 1 2 2 2 2

N 2 2 2 2 2 2 2 2 1 2 1 2 1 1 2 2 2 2 2 2 2 1 1 2 2 2

S 1 1 1 1 2 1 2 2 1 1 2 2 1 1 2 2 2 1 1 2 2 1 1 2 1 2

1 NOT CONTROL 2 CONTROL - MISSING Legend: F: Over-allocation/ Unnecessary equipment on site G: Over-allocation/ unnecessary materials on site H: Over-allocation/ unnecessary workers on site I: Unnecessary procedures and working protocols J: Material loss/ stolen from site during construction periods K: Material deterioration/ damaged during construction periods L: Mishandling or error in construction applications/ installation N: Materials for rework/ repair works/ defective works S: Accidents on site

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6.2 Construction waste control practices under direct conversion waste category

However, the analysis result still shows that there are high control exercises on direct conversion wastes as reported by the respondents. The breakdown of numbers of the

114 waste elements recognised as wastes under this direct conversion waste category are shown in Figure 6.7. From chart in Figure 7 however shows that Item F: (Overallocation/ Unnecessary equipment on site) have the highest positive counts (22 Nos) on event controlled while Item S: (Accidents on site) is recorded as the least event controlled with 12 Nos. of positive counts.

30

1 25

1

1

6

6

1

1

1

1

1

7

6

6

1

4 8 10

20

14 Missing

15

Non Control Control

22 20

10

20

19

18

20

20

16 12 5

0 F

G

H

I

J

K

L

N

S

Figure 6.7 Breakdown of direct conversion waste event control cases

By cross tabbing of both Table 6.1 & 6.2 will result in a matrix table as show in Table 6.3 below. This matrix table can be used to explain the inter-relationship between the direct conversion waste concepts of the respondents with their actual control practices on construction processes. As anticipated, there are 4 potential scenarios as observed, which are Case 1: Waste recognised and controlled; Case 2: Waste not recognised and

115 not controlled; Case 3: Waste recognised but not controlled and Case 4: Waste not recognised but controlled.

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

F

G

H

I

J

K

L

N

S 137 8 58 31 -

-

-

-

-

-

-

-

-

Case 1: Waste & Control Case 2: Non Waste & Not Control Case 3: Waste & Not Control Case 4: Non Waste & Control Matrix not available due to missing input

Legend: F: Over-allocation/ Unnecessary equipment on site G: Over-allocation/ unnecessary materials on site H: Over-allocation/ unnecessary workers on site I: Unnecessary procedures and working protocols J: Material loss/ stolen from site during construction periods K: Material deterioration/ damaged during construction periods L: Mishandling or error in construction applications/ installation N: Materials for rework/ repair works/ defective works S: Accidents on site

Table 6.3 Matrix table between waste concepts and control practices for direct conversion wastes

From the analysis, it is found that Case 1 is the most occurrence scenario with 137 cases (58.5%) followed by Case 3: 58 cases (24.8%), Case 4: 38 cases (13.2%) and finally Case 2: 8 cases (3.5%). However, These results show that over half of the direct conversion construction wastes have fully been recognised and controlled simultaneously but this analysis result is not very convincing as there are still very high

116 percentage of cases where wastes were partially recognised and controlled and not recognised and controlled at all.

117 6.2.2.2 Analysis on non-contributory time wastes

Under this category, there are only 7 wastes elements, which were asked to be identified by the respondents based on their own experience and opinion. Those items are indexed as A, B, C, D, E, M and O in the section A, B and C of the questionnaires. For the total of 27 respondents by calculation as (7 X 27), it sums up a total of 189 overall counts of inputs.

For construction waste recognition, all the inputs are tabulated in Table 6.4 below and a total of 129 positive counts are recorded or approximately 68% and it is still a high recognition on the waste concepts for the elements tested in this category but it is relatively lower in percentage compared to analysis carried out previously on direct conversion waste.

118

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

A 1 2 2 2 2 2 2 2 2 1 2 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 2

B 2 2 1 1 2 2 2 2 2 1 2 2 1 2 2 2 1 2 2 1 1 2 1 2 2 2 1

C 2 2 1 1 2 2 1 2 2 1 2 2 2 2 2 2 1 2 2 1 1 2 1 2 2 2 2

D 2 2 1 2 2 2 2 2 2 1 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2

E 1 2 1 2 2 1 2 2 2 2 2 1 1 2 2 2 2 1 2 2 2 1 1 2 2 1 2

M 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

O 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1

1 NON WASTE 2 WASTE

Legend: A: Waiting for others to complete their works before the proceeding works can be carried out B: Waiting for equipment to be delivered on site C: Waiting for materials to be delivered on site D: Waiting for the skilled workers to be on site E: Waiting for the clarification and confirmation by client and consultants M: Time for rework/ repair works/ defective works O: Time for workers’ resting during construction

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6.4 Construction waste recognition under non-contributory time waste category

The breakdown of numbers of the waste elements recognised as wastes under this noncontributory time waste category are shown in Figure 6.8. It is worthwhile to point out that most of the respondents do not recognised Item O: (Time for workers’ resting during construction) as construction as only 5 out of 27 respondents recognised it as construction waste. On the opposite side, the most recognised construction waste under this non-contributory time waste category is Item M: (Time for rework/ repair work/ defective works) which recorded a 25 positive counts out of the maximum 27.

119

30

2 4

25

6 8

9

9

20

22

Non Waste

15

Waste

25 23 21 10

18

19

18

5

5 0 A

B

C

D

E

M

O

Figure 6.8 Breakdown of non-contributory time waste recognition cases

The same reason as in direct conversion waste category analysis, the total counts for the analysis of construction waste event control will calculated with less 1 missing inputs range so it would be (7 X 26) equal to 182 total counts. All the inputs are tabulated in Table 6.5 below and a total of 148 positive counts are recorded or approximately 81% and it shows an increase in percentage on the waste event control for the elements tested compared to the construction waste recognised under this category. In other words, the respondents control non-contributory time waste more than eventually recognising them.

120 # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

A 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2

B 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

C 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 2 2 2 2 1 2 2 2 2 2 2

D 2 2 2 2 2 2 2 2 2 1 2 1 1 2 2 2 2 2 2 1 2 2 1 2 2 2

E 1 2 2 1 2 1 2 2 1 2 1 1 1 1 2 2 2 1 2 1 1 2 1 1 2 1

M 2 2 2 2 2 2 2 2 2 2 1 2 1 1 2 2 2 2 2 2 2 1 2 2 2 2

O 2 2 2 2 2 2 2 2 1 1 1 2 1 2 2 2 1 2 2 2 2 1 2 1 2 2

1 NOT CONTROL 2 CONTROL - MISSING Legend: A: Waiting for others to complete their works before the proceeding works can be carried out B: Waiting for equipment to be delivered on site C: Waiting for materials to be delivered on site D: Waiting for the skilled workers to be on site E: Waiting for the clarification and confirmation by client and consultants M: Time for rework/ repair works/ defective works O: Time for workers’ resting during construction

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6.5 Construction waste control practices under non-contributory time waste category

The breakdown of numbers of the waste elements recognised as wastes under this noncontributory time waste category are shown in Figure 6.9. It shows that Item E: (Waiting for the clarification and confirmation by client and consultants) is the least controlled waste event where more than half of the respondents reported as waste event not being controlled. Item B: (Waiting for equipment to be delivered on site) on the other hand recorded a perfect waste control event

121

30

1 1

1 0

1

1

1

1

3

25

1

4

5

7 20

14

Missing Non Control

15

25

26

Control

23

22

21

19

10

12 5

0 A

B

C

D

E

M

O

Figure 6.9 Breakdown of non-contributory time waste control practice cases

Same as direct conversion waste analysis, the cross tabbing of both Table 6.4 & 6.5 for non-contributory waste will result in a matrix table as show in Table 6.6 below. This matrix table can be used to explain the inter-relationship between the non-contributory waste concepts of the respondents with their actual control practices on construction processes. Again, 4 potential scenarios cases are to be investigated for non-contributory time waste category.

122

# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

A

B

C

D

E

M

O 107 10 24 48 -

-

-

-

-

-

-

Case 1: Waste & Control Case 2: Non Waste & Not Control Case 3: Waste & Not Control Case 4: Non Waste & Control Matrix not available due to missing input

Legend: A: Waiting for others to complete their works before the proceeding works can be carried out B: Waiting for equipment to be delivered on site C: Waiting for materials to be delivered on site D: Waiting for the skilled workers to be on site E: Waiting for the clarification and confirmation by client and consultants M: Time for rework/ repair works/ defective works O: Time for workers’ resting during construction

Table 6.6 Matrix table between waste concepts and control practices for non-contributory time wastes

From the analysis, it is found that Case 1 is the most occurrence scenario with 107 cases (56.7%) followed by Case 4: 48 cases (24.8%), Case 3: 24 cases (13.2%) and finally Case 2: 10 cases (5.3%). The result shows that about half of the non-contributory construction time wastes are recognised and controlled simultaneously and again, this results are not considered very convincing which resembles the result obtained from the matrix table for direct conversion waste as a very high percentage of cases where wastes were partially recognised and controlled and not recognised and controlled at all still existed. The obvious different between direct conversion waste analysis with non-

123 contributory waste analysis is the percentage of occurrences for Case 3 & 4. Noncontributory time waste analysis has a higher percentage of occurrences for Case 4 and a relatively low percentage of occurrences for Case 3 whereby direct conversion waste analysis has a higher percentage for Case 3 and lower for Case 4. Both Case 1 and Case 2 of the 2 analysis relative constant where Case 1 stays around 57% – 58% and Case 2 at a low 3.5% - 5%

124 6.2.2.3 Analysis on contributory time wastes

Under this category, there are only 3 wastes elements, which were asked to be identified by the respondents based on their own experience and opinion. Those items are indexed as P, Q & R in the section A, B and C of the questionnaires. For the total of 27 respondents by calculation as (3 X 27), it sums up a total of 81 overall counts of inputs. For construction waste recognition, all the inputs are tabulated in Table 6.7 below and a total of 10 positive counts are recorded or approximately 12% and this a very low recognition on the waste concepts for the elements tested under this category compared to analysis carried out previously on direct conversion waste and non-contributory time waste where both categories are above 70 % - 80% of recognition.

125

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

P 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Q 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 1 2 1 1

R 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1

1 2

NON WASTE WASTE

Legend: P: Time in supervising and inspecting the construction works Q: Time for instructions and communication among different tiers and trades of workers R: Time for transporting workers, equipment and materials

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6. 7 Construction waste recognition under contributory time waste category

The breakdown of numbers of the waste elements recognised as wastes under this contributory time waste category are shown in Figure 6.10. It is not surprising to see that all the 3 items registered under contributory time wastes are recording significant negative counts, which represent non waste recognition for the contributory time wastes. Very much different with the first 2 waste recognition analysis, all 3 items are recording high negative counts that above 20 counts where Item P: (Time in supervising and inspecting the construction works) with the greatest numbers of negative counts (26 Nos.) followed by Item R: (Time for transporting workers, equipment and materials) –

126 23 Nos. and Item Q: (Time for instructions and communication among different tiers and trades of workers) – 22 Nos.

30

25

20

22

23

26

15

Non Waste Waste

10

5

5

4

1 0 P

Q

R

Figure 6.10 Breakdown of contributory time waste recognition cases

The total counts for the analysis of construction waste event control will calculated with less 1 missing inputs range so it would be (3 X 26) equal to 78 total counts. All the inputs are tabulated in Table 6.8 below and a total of 69 positive counts are recorded or approximately 88% and it shows an tremendous increase in percentage on the waste event control for the elements tested compared to the construction waste recognised under this category. This vast contrast of percentages between wastes recognition and waste event control under this category suggested that the respondents do not see

127 contributory time wastes as a waste but in actual practices, they obvious notices the important of controlling those events.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

2P 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2

2Q 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 2

2R 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

1 2

NOT CONTROL CONTROL

Legend: P: Time in supervising and inspecting the construction works Q: Time for instructions and communication among different tiers and trades of workers R: Time for transporting workers, equipment and materials

Note: The values given in the table do not have any significant meaning in this descriptive statistic analysis, as they are values inputs for inferential statistic analysis later in the chapter

Table 6.8 Construction waste control practices under contributory time waste category

The breakdown of numbers of the waste elements recognised as wastes under this noncontributory time waste category are shown in Figure 6.11. It shows that all the 3 items are having high positive counts for waste event control where all 3 items of contributory time waste are recording above 20 Nos. of positive counts lead by Item P: (Time in supervising and inspecting the construction works) with 25 Nos.

128

30

1 1 25

1

1

5

4

20

Missing Non Control

15

25 22

21

Control

10

5

0 P

Q

R

Figure 6.11 Breakdown of contributory time waste control practice cases

Again, by cross tabbing of both Table 6.7 & 6.8 for contributory waste will result in a matrix table as show in Table 6.9 below. Therefore, the inter-relationship between the contributory waste concepts of the respondents with their actual control practices on construction processes can be explained using this matrix table. 4 potential scenarios cases are to be investigated for contributory time waste category.

129

P 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Q

R 7 6 3 62 -

-

-

Case 1: Waste & Control Case 2: Non Waste & Not Control Case 3: Waste & Not Control Case 4: Non Waste & Control Matrix not available due to missing input

Legend: P: Time in supervising and inspecting the construction works Q: Time for instructions and communication among different tiers and trades of workers R: Time for transporting workers, equipment and materials

Table 6.9 Matrix table between waste concepts and control practices for contributory time wastes

From the analysis, it is found that Case 4 is the most occurrence scenario with 62 cases (79.5%) followed by Case 1: 7 cases (9.0%), Case 2: 6 cases (7.7%) and finally Case 3: 3 cases (3.8%). The result shows that contributory time wastes has not been regarded as construction wastes by most of the respondents. Nevertheless, in actual practices, they seek to control those particular waste elements under contributory time wastes category, which explained that they subconsciously acknowledged the important of controlling those elements in their construction processes.

130 If we study the overall waste recognition, it is found that the percentage of project management orientated personnel will have a slightly higher percentage of construction waste recognition (72.6%) over site operative management orientated personnel (61.7%) (Refer Figure 6.12 below)

100% 90%

73 97

80%

(27.4%) (39.3%)

70% 60%

non waste waste

50% 40% 30%

193

(72.6%)

150

(61.7%)

20% 10% 0% Project Management Orientated Position

Site Management Orientated Position

Figure 6.12 Percentage breakdown of the wastes recognition by nature of work of the respondents

However, in certain wastes elements, site operative management personnel were recorded higher recognition percentage compared to project management personnel for example Item 1S: (Accidents on site), site operative management personnel were recorded (13 out of 13) 100% recognition compared to project management personnel only recorded (10 out of 14) 71.4% of recognition for that particular items.

131 6.3 Inferential analysis results

This section will discuss about the analysis results from inferential analysis. Statistic tools such as correlation Pearson-r and One-Way t-test will be utilised to test some hypotheses of the study and determine the frequency ranking of each particular event or case as rated by the respondents.

6.3.1 Correlation among direct conversion wastes concepts and perceptions, waste event control and frequencies of waste event occurrences

There are 3 hypotheses to be tested under this direct conversion wastes category:

Hypothesis 1: There is inter-relationship between construction’s direct conversion wastes are been perceived (D_WASTE1) with the tendency to control those wastes (D_WASTE2) Hypothesis 2: There is inter-relationship between construction’s direct conversion wastes are been perceived (D_WASTE1) with the frequencies of occurrences of such wastes during the processes (D_WASTE3) Hypothesis 3: There is inter-relationship between the tendency to control those construction’s direct conversion wastes (D_WASTE2) with the frequencies of occurrences of such wastes during the processes (D_WASTE3)

132 The purpose of these 3 hypotheses is to study whether any significant correlation existed among waste conception, waste event control and the frequencies of wastes events occurrences. These 3 hypotheses are to be tested together using correlation Pearson r, and the results show that there are not significant correlations among each other (refer Table 6.10) as the two-tail sig. value (K) is more than 0.05 for 3 cases tested. Hence Hypothesis 1, 2 and 3 is rejected. Hypothesis 1 Test Variables

D_WASTE1

D_WASTE2

-.193

K = .364 >.05 Hypothesis 2 Test Variables

D_WASTE1

D_WASTE3

-.040

K = .842 >.05 Hypothesis 3 Test Variables

D_WASTE2

D_WASTE3

-.080

K = .698 >.05

Table 6.10 Correlation Pearson-r results summaries for hypothesis 1, 2 and 3 (Refer Appendix 1 for Correlation Pearson-r result outputs from SPSS 10.0)

133 6.3.2 Correlation among non-contributory time wastes concepts and perceptions, waste event control and frequencies of waste event occurrences

Same as direct conversion wastes, there are 3 hypotheses to be tested under this noncontributory wastes category:

Hypothesis 4: There is inter-relationship between construction’s non-contributory time wastes are been perceived (NON_CON1) with the tendency to control those wastes (NON_CON2) Hypothesis 5: There is inter-relationship between construction’s non-contributory time wastes are been perceived (NON_CON1) with the frequencies of occurrences of such wastes during the processes (NON_CON3) Hypothesis 6: There is inter-relationship between the tendency to control those construction’s non-contributory time wastes (NON_CON2) with the frequencies of occurrences of such wastes during the processes (NON_CON3)

The purpose of these 3 hypotheses is to study whether any significant correlation existed among waste conception, waste event control and the frequencies of wastes events occurrences. These 3 hypotheses are to be tested together using correlation Pearson r, and the results show that there are not significant correlations among each

134 other (refer Table 6.11) as the two-tail sig. value (K) is more than 0.05 for 3 cases tested. Hence Hypothesis 4, 5 and 6 is rejected.

Hypothesis 4 Test Variables

NON_CON1

NON_CON2

-.003

K = .989 >.05 Hypothesis 5 Test Variables

NON_CON1

NON_CON3

-.291

K = .141 >.05 Hypothesis 6 Test Variables

NON_CON2

NON_CON3

.297

K = .141 >.05

Table 6.11 Correlation Pearson-r results summaries for hypothesis 4, 5 and 6 (Refer Appendix 1 for Correlation Pearson-r result outputs from SPSS 10.0)

135 6.3.3 Correlation among contributory time wastes concepts and perceptions, waste event control and frequencies of waste event occurrences

Same as previous 2 wastes categories, there are 3 hypotheses to be tested under this contributory wastes category:

Hypothesis 7: There is inter-relationship between construction’s contributory time wastes are been perceived (CON1) with the tendency to control those wastes (CON2) Hypothesis 8: There is inter-relationship between construction’s contributory time wastes are been perceived (CON1) with the frequencies of occurrences of such wastes during the processes (CON3) Hypothesis 9: There is inter-relationship between the tendency to control those construction’s contributory time wastes (CON2) with the frequencies of occurrences of such wastes during the processes (CON3) The purpose of these 3 hypotheses is to study whether any significant correlation existed among waste conception, waste event control and the frequencies of wastes events occurrences. These 3 hypotheses are to be tested together using correlation Pearson r, and the results show that there are significant correlations between the way contributory time wastes have been perceived (CON1) with the tendency to control those wastes (CON2) as the 2-tail sig. value (K) signify the correlation is significant at 0.01 level or value K < 0.01 with a negative correlation (r = -.551) whereas the other 2

136 cases are tested non-significant with the 2-tail sig. value (K) is more than 0.05. (Refer Table 6.12) Hence Hypothesis 7 is accepted and hypothesis 8 and 9 is rejected. The case of Hypothesis 7 is true if we look back at the matrix table for contributory time waste (Table 6.9) which also indicated that the most cases recorded among the cross tabbing exercises proved that Case 4: Wastes not recognised but controlled is among the most registered cases whereby in term of count inputs, it should be results in a negative counts for wastes recognition and positive counts for wastes event control for a overall negative correlation. Hypothesis 7 Test Variables

CON1

CON2

-.551**

K = .004 >.01** Hypothesis 8 Test Variables

CON1

CON3

-.223

K = .263 >.05 Hypothesis 9 Test Variables

CON2

CON3

.268

K = .185 >.05

Table 6.12 Correlation Pearson-r results summaries for hypothesis 7, 8 and 9 (Refer Appendix 1 for Correlation Pearson-r result outputs from SPSS 10.0)

137 6.3.4 Ranking on frequencies of occurrences for wastes exist in construction processes

The purpose of this analysis is to determine the frequency of occurrences of construction wastes as experienced by the respondents, the frequencies of occurrences for construction wastes are analysed by using one-way t-test to determine the mean values, standard of deviation and standard error mean and the mean of scores were listed in descending order as shown in Table 6.13

#

Construction Waste Variables

P3 Time in supervising and inspecting the E3 Q3 A3 M3 N3 C3 R3 B3 K3 J3 L3 I3 O3 G3 D3 S3 F3 H3

construction works Waiting for the clarification and confirmation by client and consultants Time for instructions and communication among different tiers and trades of workers Waiting for others to complete their works before the proceeding works can be carried out Time for rework/ repair works/ defective works Materials for rework/ repair works/ defective works Waiting for materials to be delivered on site Time for transporting workers, equipment and materials Waiting for equipment to be delivered on site Material deterioration/ damaged during construction periods Material loss/ stolen from site during construction periods Mishandling or error in construction applications/ installation Unnecessary procedures and working protocols Time for workers’ resting during construction Over-allocation/ unnecessary materials on site Waiting for the skilled workers to be on site Accidents on site Over-allocation/ unnecessary equipment on site Over-allocation/ unnecessary workers on site

N

Mean 4.00

Std. Deviation .83

Std. Error Mean .16

27

Waste Categories Contributory Time

27

3.81

.79

.15

Non-Contributory Time

27

3.78

.75

.14

Contributory Time

27

3.67

.73

.14

Non-Contributory Time

27 27

3.37 3.33

.69 .73

.13 .14

Non-Contributory Time Direct Conversion

27 27

3.30 3.26

.95 .94

.18 .18

Non-Contributory Time Contributory Time

27 27

3.15 3.11

.86 .89

.17 .17

Non-Contributory Time Direct Conversion

27

3.07

.83

.16

Direct Conversion

27

3.04

.90

.17

Direct Conversion

27 27 27 27 27 27 27

3.00 2.96 2.93 2.67 2.52 2.44 2.41

.96 .85 .83 .92 .70 .85 .84

.18 .16 .16 .18 .13 .16 .16

Direct Conversion Non-Contributory Time Direct Conversion Non-Contributory Time Direct Conversion Direct Conversion Direct Conversion

Table 6.13 Construction waste variables ranking (Refer Appendix 2 for t-test results output from SPSS 10.0)

138

From the mean ranking results, it shows that time wastes categories regardless of contributory time or non-contributory time wastes occurred at the top of the list compared to direct conversion wastes. Therefore, it is recommended that for construction processes improvements, it is eventually those contributory and noncontributory times waste variables that have to be given more attentions and in real fact, most of them are related to process flows and sequences and this can lead to lean construction’s tools and methods which are developed mostly to tackle those wastes resulted from process flow inefficiencies.

139 6.3.5 Ranking on likeliness for sources/ causes for the construction wastes

The purpose of this analysis is to determine the respondent’s recognition of particular sources/ causes factors that cause construction wastes. Same as ranking for the frequencies of wastes occurrences, the rating on these likelihood of waste sources/ causes factors as rated by the respondents are analysed by using one-way t-test and the mean of scores were listed in descending order as shown in Table 6.14 #

N

Mean

E2 Late information and decision making

27

3.63

D2 Poorly scheduled delivery of material to site A1 Poor coordination among project participants

27 27

3.37 3.37

E3 Unclear information

27

3.26

A2 Poor planning and scheduling

27

3.26

D3 Poor quality of material A3 Lack of control

27 26

3.26 3.23

D1 Delay of material delivery E1 Defective or Wrong information

27 27

3.22 3.15

27 27 27 27 27 27 27 27 27 27 27 27 27

3.11 3.11 3.07 3.04 2.96 2.93 2.93 2.93 2.93 2.89 2.85 2.81 2.78

27 27 27

2.70 2.67 2.52

B2 D4 D6 B3 B5 B4 B1 C3 D5 C6 C5 C4 A4

Sources/ Causes for Construction Wastes

Inexperience inspectors Poor equipment choice or ineffective equipment Poor site documentation Too few supervisors/ foreman Supervision too late Uncontrolled sub-contracting practices Lack of trades skills Equipment shortage Poor storage of material Poor site documentation Poor site layout and setting out Poor equipment choice or ineffective equipment Bureaucracy

B6 Poor labour distribution C1 Inappropriate construction methods C2 Outdated equipment

Std. Std. Error Sources/ Causes Factors Deviation Mean Categories .56 .11 Information and Communication Factors .63 .12 Material Factors .63 .12 Management & Administration Factors .53 .10 Information and Communication Factors .59 .11 Management & Administration Factors .71 .14 Material Factors .59 .12 Management & Administration Factors .70 .13 Material Factors .53 .10 Information and Communication Factors .51 9.75E-02 People Factors .80 .15 Material Factors .68 .13 Material Factors .59 .11 People Factors .71 .14 People Factors .62 .12 People Factors .62 .12 People Factors .62 .12 Execution Factors .73 .14 Material Factors .58 .11 Execution Factors .66 .13 Execution Factors .56 .11 Execution Factors .58 .11 Management & Administration Factors .67 .13 People Factors .73 .14 Execution Factors .80 .15 Execution Factors

Table 6.14 Sources/ causes of construction waste ranking (Refer Appendix 2 for t-tests results output from SPSS 10.0)

140 As from the mean ranking result shows that Item E2: (Late information and decision making) is highly regarded as the main contributory sources or causes to the construction wastes with the highest mean value (3.63) and with a 0.26 from the second rank item D2: (Poorly scheduled delivery of material to site)

Among the clusters of cause factors observed from Table 6.14, there are 3 categories of waste sources/ causes factors are widely acknowledged as the key contributory factors to construction wastes. Those categories included Information and Communication Factors, Management and Administration Factors and Material Factors as most of the Cause factors captured under these 3 categories are rated with the mean value over 3.

Overall, the likelihood of recognising the items above as the sources/ causes of wastes that will impact on the productivity of the projects, are still reasonably high as most of the mean value for the items tested were clustering around the scale “3” value representing “likely as a sources/ causes of wastes”. However, there are also some exceptions such as Item C1: (Inappropriate construction methods) and Item C2: (Outdated equipment) both recorded a slightly low mean values of 2.67 and 2.52 respectively.

141 6.4 Causes and Effects Matrix

The purpose of this analysis to relate the particular sources or causes to the construction wastes and this is to give us a better picture of what leads to the waste in construction processes as suggested by the respondents feedback on this research. Figure 6.13 is the overall analysis on Causes and Effects Matrix of the “Major cause” to the construction wastes based on 5 main causes factors while Figure 6.14 is the Causes and Effects Matrix of the “Other causes” to the construction wastes. (Refer overall Causes and Effects Matrix tables in Appendix 4 for a detailed understanding on actual one to one relationship between wastes causes to wastes itself as per the data gather from the respondents of this research)

142

Management & Administration Factors People Factors

R Q

Execution Factors

P

Materials Factors

O

Information & Communication Factors

N

Not relevant

Type of Construction Wastes

M L K

Legend: J I H G F E D C B A 0

5

10

15

Nos. of major cause related

20

A: Waiting for others to complete their works before the proceeding works can be carried out B: Waiting for equipment to be delivered on site C: Waiting for materials to be delivered on site D: Waiting for the skilled workers to be on site E: Waiting for the clarification and confirmation by client/ consultants F: Over-allocation/ unnecessary equipment on site G: Over-allocation/ unnecessary materials on site H: Over-allocation/ unnecessary workers on site I: Unnecessary procedures and working protocols J: Material loss/ stolen from site during construction periods K: Material deterioration/ damaged during construction periods L: Mishandling or error in construction applications/ installation M: Rework/ repair works/ defective works N: Workers’ resting during construction O: Supervising and inspecting the construction works 25P: Instructions and communication among different tiers and trades of workers Q: Transporting workers, equipment and materials R: Accidents on site

Figure 6.13 Causes and Effects relationship for the cases of major causes (Categorised)

143

Management & Administration Factors People Factors

R Q

Execution Factors

P Materials Factors O Information & Communication Factors

N

Types of construction wastes

M

Not relevant

L Legend:

K J I H G F E D C B A 0

5

10

15

20

25

Nos. of other causes related

30

A: Waiting for others to complete their works before the proceeding works can be carried out B: Waiting for equipment to be delivered on site C: Waiting for materials to be delivered on site D: Waiting for the skilled workers to be on site E: Waiting for the clarification and confirmation by client/ consultants F: Over-allocation/ unnecessary equipment on site G: Over-allocation/ unnecessary materials on site H: Over-allocation/ unnecessary workers on site I: Unnecessary procedures and working protocols J: Material loss/ stolen from site during construction periods K: Material deterioration/ damaged during construction periods L: Mishandling or error in construction applications/ installation M: Rework/ repair works/ defective works N: Workers’ resting during construction O: Supervising and inspecting the construction works P: Instructions and communication among different 35 tiers and trades of workers Q: Transporting workers, equipment and materials R: Accidents on site

Figure 6.14 Causes and Effects relationship for the cases of others causes (Categorised)

The matrix table provides a clearer insight into the types of causes factors that directly related construction wastes, as we shall see that in Figure 6.13, Management and Administration Factors has a relatively high counts numbers in causing the construction wastes items ranging from Item A to Item I and Item Q, Materials Factors dominants over Item J & K and People Factors score higher in Item M, N and O. By conducting

144 this causes and effects matrix exercise, we can know that each types of construction wastes has a different roots causes to the problems and it is important to identify those particular causes to the problems in order to a proper corrective or preventive actions can be carried to ensure continuous improvement in performance of construction activities.

145 CHAPTER 7

CONCLUSIONS AND RECOMMENDATIONS

7.1 Introduction

This chapter concludes the whole study based on the findings. The tested hypotheses will be related to the research objectives and further interpreted and conclusion on the achievement of the research objectives will be drawn. Some recommendations will also be drawn from the findings and the limitations during the research period will also be highlighted

7.2 Discussions of the findings of the research

The discussion on the findings of the research will be carried in 2 separate ways: 1. Relating the research findings to research objectives 2. Rewritten hypotheses and interpret the results

7.2.1 Relating the research findings to research objectives

1. Research objective 1: General perceptions on construction wastes based on lean construction principles

146 From the research results, it is found that the general perceptions and lean concepts of local construction personnel particularly on construction wastes and their tendency to control these wastes are at an acceptable level. The local construction site personnel can identified most wastes as outlined and the tendency of controlling those wastes is even higher than recognising the wastes themselves. However, from the results, it also shows that the recognition over flow related construction wastes is rather low compared to direct conversion wastes or physical wastes especially those related to contributory time wastes. This signify that the local construction personnel are still not fully comprehend the concepts of flows and non value-adding activities and tends to included these contributory work as part and parcel of conversion process.

In fact, lean construction philosophy sees these contributory works as not adding any values to the client even though they are sometimes necessary for the progress of the overall construction processes. On the bright side, the research results also show a very high percentage on those contributory works as being controlled during the construction processes signaling that those contributory time wastes are actually well aware off those activities even though they being not recognised as construction wastes.

Besides that, it is also found that there are different levels of waste recognition between project management orientated personnel and the site

147 operative management orientated personnel. Project managerial personnel recorded higher overall waste recognition compared to site operative managerial personnel suggesting that they are more sensitive to overall construction wastes issues and those related to process flows, whereas site operative managerial personnel are found more concentrated for conversion wastes where the percentage of recognising some conversion wastes are higher than the project managerial personnel.

2. Research Objective 2: Degree of problems arisen of the wastes identified

Based on the ranking of the event occurrences frequencies for waste events existed in construction processes shows that the most frequent waste events occurred in construction activities are actually flow related with both contributory time wastes and non-contributory time wastes were at the top of the ranking list. On the other hand, many direct conversion wastes are recorded rather low scores mostly in the range of “Seldom” and “Very Rare” occurrence events.

Eventually by breaking down the waste categories, it is made clear that the flow time wastes are the prominent events that occurred in construction processes. Therefore, based on that information, a better performance improvement strategies can be arranged to target at those flow related wastes events, as those events are usually invisible or ignored by

148 conventional construction management. The construction processes can be further streamlined by reducing or eliminating those flow waste elements by implementing the lean construction principles and practices such as employee involvements, kanzan, JIT concepts etc at all level of construction processes.

3. Research Objective 3 & 4: Waste cause and effect relationship and potential improvement strategies

In this research, major sources of wastes are also been identified directly related to the respective construction wastes from the wastes causes and effects matrix as shown in Appendix 4. From the aggregated results shows that management and administrative factors are recognised as the dominant sources of wastes for most of the cases while material factors and people factors are more dominant for a few wastes types. If compared to the ranking of the likelihood for waste factors to impact the construction productivity in general, information and communications factors which are hardly seen as a dominant factor of any construction wastes types at the top of the ranking list follow tightly by management and administrative factors. On the low side, the executive factors and people factors scored relatively low in the ranking.

149 This is a very good exercise to point out the causes and effects relationship between the sources of waste and waste itself for processes control, reengineering or redesign by targeting directly at the respective sources of wastes for processes improvement. In most leaner construction organisition, they usually practise this exercise in a survey called waste identification survey (WIS) through work sampling practices in order to monitor and improve their flow performance from time to time during their construction activities.

7.2.2

Rewritten hypotheses and interpret the results

From inferential statistical analyses in chapter 6, 9 hypotheses testing were conducted with Pearson-r correlation. The results from the analyses had concluded following hypotheses as:

For direct conversion wastes inter-relationship testing 1. There is no significant inter-relationship between construction’s direct conversion wastes perceived with the tendency to control those wastes. 2. There is no significant inter-relationship between construction’s direct conversion wastes perceived with the frequencies of occurrences of such wastes during construction.

150 3. There is no significant inter-relationship between the tendency to control direct conversion wastes with the frequencies of occurrences of such wastes during construction.

For non-contributory time wastes inter-relationship testing 4. There is no significant inter-relationship between construction’s noncontributory time wastes perceived with the tendency to control those wastes. 5. There is no significant inter-relationship between construction’s noncontributory time wastes perceived with the frequencies of occurrences of such wastes during construction. 6. There is no significant inter-relationship between the tendency to control non-contributory time wastes with the frequencies of occurrences of such wastes during construction.

For contributory time wastes inter-relationship testing 7. There is no significant inter-relationship between construction’s contributory time wastes perceived with the tendency to control those wastes. 8. There is no significant inter-relationship between construction’s contributory time wastes perceived with the frequencies of occurrences of such wastes during construction.

151 9. There is significant inter-relationship between the tendency to control contributory time wastes with the frequencies of occurrences of such wastes during construction.

The non-significant over almost all the hypotheses tested (except contributory time wastes recognition and control recorded a negative significant score or -.551) in correlation testing shows that there were not uniformity in the way the construction waste are recognised and controlled even with the high recognition and control rates. Recognising particular construction wastes or frequencies of occurrence of construction wastes on site by the construction personnel do not prompt them to control them and vice versa, recognizing construction wastes are not prompt by the frequencies of occurrence of those wastes during construction site. The construction wastes are treated very subjectively from cases to cases and suggested that no proper doctrine or philosophy in supporting for particular waste recognition and control mechanism.

In the importance of continuous process and productivity improvement, having the correct concepts and understanding and having the right attitudes to mitigate and control the flow and flow related wastes are very essence. In this case, the worst scenario would be someone actually not knowing what is the waste and therefore not put in any efforts to control it and letting the wastes to repeat from time to time. There might be some other reasons for not recognising wastes and not controlling them. Some would not treat it as a waste as those wastes are

152 recoverable due to defaults by others and some misunderstanding that wastes are necessary to avoid others bigger wastes from happening. For example, as cited from the only 1 qualitative inputs from all 27 questionnaires received stated that waiting for clarification and confirmation by client and consultants is not a waste because he/ she believed that it is important to wait for clarification and confirmation “because lack of this will be more wastage (redo the task)”. From the results of cross-tab matrix tables shows a relatively low percentage of that particular scenario (less than 7%) and that should be a good sign for the local construction industries.

However, for the scenarios of knowing the wastes but not controlling them hit a rather high numbers of cases and percentage especially in direct conversion wastes. This is particularly not a good sign where those wastes are left behind the construction processes and hinder the full potential of process improvement. The results to this might be abundant. One of the reason would be the costs to control or improve the wastes might be higher that the cost of the wastes itself. Besides that, the reasons of not control the wastes even the wastes are identified and recognised perhaps is due to not sufficient tools and knowledge to control them and some might due to misunderstanding during execution and not well trained personnel.

153 7.3 Limitations of the research

One of the limitations to this research is the design of the research by trying to discuss lean construction philosophy in a general perceptive of construction processes, which restricted to site construction processes only. In the real essences of lean construction, lean construction principles are universal and can be applied in all aspects of construction processes flow improvement from the very start of the projects until the very end of project execution and delivery. In that context, the overall process flow improvement can include design management, supply chain management, sub-contracting management etc and not just restricted to wastes of the area of this study.

In that bigger extent of interpretation on lean construction, the potential productivity improvement is even greater but it required a higher degree of commitment and leadership while this research is only focusing one main concept of flow as suggested by lean construction and studies the related perceptions and actual control practices on flow related wastes as well as the potential improvement available based on the findings of the research.

The other limitations to this study is the lack of qualitative data on this research, those qualitative data can be useful in answering certain reasons behind of particular understanding, attitudes and actions by the respondents. In this research, only one qualitative data are provided among all respondents although in the

154 questionnaire has prepared column for the respondents to express their views and opinions.

7.4 Challenges in Implementing Lean Construction

There have been many general principles of lean construction highlighted in the previous chapters. The principles cited relate to three broad areas: improving the activity or task (workstation) operation, optimising the overall process, and learning from external facilities and organisations (benchmarking). Different principles apply at each level, and the concepts upon which these principles are based may also differ. For example, at the total process level, construction can be viewed as a series of sequential operations whereas at the activity and subtask levels, the work is largely composed of concurrent operations. Also, at the total process level, analyses of the work tend to be process oriented. At the activity level, analyses are more product-oriented.

Due to the diffusing concepts and principles of lean construction, Implementing it into the existing processes will somehow turn out to be more difficult especially this implementation is something which has to deal with mindset and culture changes. Therefore, it is outlined with a few key challenges that need to be seriously looked into in order to successfully adopt and implement the new philosophy of lean construction into the conventional practices.

155 1. Management commitment Leadership is needed to realise a fundamental shift of philosophy, with the goal of improving every activity in the organisation. Without an active initiative from the management, change will stop at all natural barriers. Management must understand and internalise the new philosophy. The change will be realised only through people; it cannot be delegated to staff specialists, like in the case of investment into new technology. Management must create an environment, which is conducive to change.

2. Focus on measurable and actionable improvement The focus should be on actionable and measurable improvement, rather than just on developing capabilities. Of course, defining various flow processes and focusing on their bottlenecks to speed up and smooth out material and information flows means just that. Short-term successes then reinforce motivation for further improvement.

Originally in JIT, the overarching goal was to reduce or eliminate inventories. However, reduction of inventories uncovered other problems, which had to be solved as a forced response. Cycle time, space and variability have also been used as drivers, because they too are increased by underlying problems. Especially cycle time provides an excellent, easy to understand driver, which can be improved continually.

156 3. Involvement Employee involvement happens naturally, when organisational hierarchies are dismantled, and the new organisation is formed with self-directed teams, responsible for control and improvement of their process. But also even if the hierarchy remains intact, involvement can be stimulated through problem solving teams. Employee involvement is thus necessary, but not sufficient for realising the full potential of continuous improvement.

4. Learning Implementation requires a substantial amount of learning. First, learning should be directed at principles, tools and techniques of process improvement. In the next phase, the focus turns to empirical

xi

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Abdul Rashid Abdul Aziz and Abdul Aziz Hussin, (2003) “Construction Safety In Malaysia: A Review Of Industry Performance And Outlook For The Future” in Journel of Construction Research, 4(2), pp.146-148 Adrian , James.J., (1987) Construction Productivity Improvement, Elsevier Science Publishing, New York Alarcón, Luis F. (1993). “Modeling waste and performance in construction.” In Lean Construction, Alarcón (Ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997 Alarcón, Luis F. (1994). “Tools for the identification and reduction of waste in construction projects.” In Lean Construction, Alarcón (Ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997 Alarcón, Luis F. (1995). “Training field personnel to identify waste and improvement opportunities in construction.” In Lean Construction, Alarcón (Ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997 Alwi, Hampson & Mohamed (2002) Waste in the Indonesian construction projects Website: www.odsf.co.za/w107/Authors/Accepted%20Papers/063p%20%20final.doc Conte, Antonio Sergio Itri and Gransberg, Douglas (2001) “Lean construction: From theory to practice.” AACE International Transactions, Morgantown Cusumano, Michael A and Nobeoka, Kentaro, (1998) Thinking Beyond Lean, The Free Press, New York Department of the Environment, Transport and the Regions (DETR) (1998). Rethinking Construction. DETR Home page, U.K. quoted in Banik, Gouranga C., (1999) “Construction Productivity Improvement”, ASC Proceedings of the 35th Annual Conference, pg 165 – 178 Enton, David (1994). “Lean production productivity improvements for construction professions” In Lean Construction, Alarcón (ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997. Ford, H., (1926) “Today and Tomorrow”, Doubleday, Garden City, N.Y. quoted in Formosa, Carlos T et al (2002) “Material waste in building industry: main causes and prevention.” In Journel of Construction Engineering and Management, July/ August, pp. 317

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Formosa, Carlos T et al (1999) “Method of waste control in the building industry.” In Proceedings ICLG-7, University of California, Berkeley, CA, USA, pp. 325-334 Formosa, Carlos T et al (2002) “Material waste in building industry: main causes and prevention.” In Journel of Construction Engineering and Management, July/ August, pp. 316-318 Freeman, Miller (1999). “Best Practice: Thinking lean” in What’s New in Building, Feb 1, 1999, pp. 48 Kiess, Harold O., (1989) Statistical Concepts for The Behavioral Sciences, Allyn & Bacon, Inc. Massachusetts Koskela, Lauri (1993).”Lean production in construction.” In Lean Construction, Alarcón (ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997. Koskela, Lauri (1992). Application of new production philosophy to construction Tech. Rep. No 72, CIFE, Stanford, California Koskela, Lauri (2000). An Exploration towards a production theory and its application to construction, VTT Publication 408, Espoo, Finland Website: http://www.inf.vtt.fi/pdf/publications/2000/P408.pdf Koskela, Lauri & Howell Gregory (2002). The Underlying Theory of Project Management is Obsolete. Website: http://www.leanconstruction.com/pdf/obsoletetheory/pdf Love, Peter E D, Irani Zahir & Edwards David J (2003) “Learning to reduce rework in projects: Analysis of firm’s organizational learning and quality practices.” In Project Management Journal, September, pp. 13-25 Shingo, Shigeo (1981), “Toyota Manufacturing System”, quoted in Alarcón, Luis F. (1994). “Tools for the identification and reduction of waste in construction projects.” In Lean Construction, Alarcón (Ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997 pg.369 Plossl, George W., (1991) “Managing in the new world of manufacturing”, PrenticeHall, Englewood Cliffs, quoted in Alarcón, Luis F. (1994). “Tools for the identification and reduction of waste in construction projects.” In Lean Construction, Alarcón (Ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997 pg.369 Taylor, T.W., (1913) “The principles of scientific management”, Harper and Brothers, New York quoted in Formosa, Carlos T et al (2002) “Material waste in building industry: main causes and prevention.” In Journel of Construction Engineering and Management, July/ August, pp. 317

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Serpell, Alfredo, Venturi, Adriano & Contreras, Jeanette. (1995). “Characterization of waste in building construction projects.” In Lean Construction, Alarcón (ed.), A.A. Balkema, Rotterdam, The Netherlands, 1997. Womack, J and Jones, D. (1996). Lean Thinking. Simon & Schuster Wright, Gordon (2000). “Lean construction boosts productivity” in Building Design & Construction, 41(12), pp.29-32

xiv

APPENDIX 1: CORRELATION PEARSON R RESULTS FROM SPSS 10.0 Correlations D_WASTE1 Pearson Correlation Sig. (2-tailed) N D_WASTE2 Pearson Correlation Sig. (2-tailed) N D_WASTE3 Pearson Correlation Sig. (2-tailed) N

D_WASTE1 D_WASTE2 D_WASTE3 1.000 -.193 -.040 . .346 .842 27 26 27 -.193 1.000 -.080 .346 . .698 26 26 26 -.040 -.080 1.000 .842 .698 . 27 26 27

Correlations NON_CON1 Pearson Correlation Sig. (2-tailed) N NON_CON2 Pearson Correlation Sig. (2-tailed) N NON_CON3 Pearson Correlation Sig. (2-tailed) N

NON_CON1 NON_CON2 NON_CON3 1.000 -.003 -.291 . .989 .141 27 26 27 -.003 1.000 .297 .989 . .141 26 26 26 -.291 .297 1.000 .141 .141 . 27 26 27

Correlations CON1 CON2 Pearson Correlation 1.000 -.551** Sig. (2-tailed) . .004 N 27 26 CON2 Pearson Correlation -.551** 1.000 Sig. (2-tailed) .004 . N 26 26 CON3 Pearson Correlation -.223 .268 Sig. (2-tailed) .263 .185 N 27 26 ** Correlation is significant at the 0.01 level (2-tailed). CON1

CON3 -.223 .263 27 .268 .185 26 1.000 . 27

xv APPENDIX 2 ONE-WAY T-TEST RESULTS FROM SPSS 10.0 One-Sample Statistics N A3 B3 C3 D3 E3 F3 G3 H3 I3 J3 K3 L3 M3 N3 O3 P3 Q3 R3 S3

Mean 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27

3.67 3.15 3.30 2.67 3.81 2.44 2.93 2.41 3.00 3.07 3.11 3.04 3.37 3.33 2.96 4.00 3.78 3.26 2.52

Std. Deviation .73 .86 .95 .92 .79 .85 .83 .84 .96 .83 .89 .90 .69 .73 .85 .83 .75 .94 .70

Std. Error Mean .14 .17 .18 .18 .15 .16 .16 .16 .18 .16 .17 .17 .13 .14 .16 .16 .14 .18 .13

One-Sample Statistics N A4_1 A4_2 A4_3 A4_4 B4_1 B4_2 B4_3 B4_4 B4_5 B4_6 C4_1 C4_2 C4_3 C4_4 C4_5 C4_6 D4_1 D4_2 D4_3 D4_4 D4_5 D4_6 E4_1 E4_2 E4_3

Mean 27 27 26 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27

3.37 3.26 3.23 2.78 2.93 3.11 3.04 2.93 2.96 2.70 2.67 2.52 2.93 2.81 2.85 2.89 3.22 3.37 3.26 3.11 2.93 3.07 3.15 3.63 3.26

Std. Deviation .63 .59 .59 .58 .62 .51 .59 .62 .71 .67 .73 .80 .62 .56 .66 .58 .70 .63 .71 .80 .73 .68 .53 .56 .53

Std. Error Mean .12 .11 .12 .11 .12 9.75E-02 .11 .12 .14 .13 .14 .15 .12 .11 .13 .11 .13 .12 .14 .15 .14 .13 .10 .11 .10

xvi APPENDIX 3 SPSS DATA INPUT SHEETS (RESPONDENT’S INFO) POSITION

P_TYPE

CIDB

CLIENT

1

4

2

2

1

4

2

2

2

3

2

1

1

1

2

1

2

5

2

2

1

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1

4

1

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2

4

2

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2

2

-

1

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3

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4

-

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5

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1

xvii APPENDIX 3 SPSS DATA INPUT SHEETS (CONT’D) (WASTE CONCEPTS) A1

B1

C1

D1

E1

F1

G1

H1

I1

J1

K1

L1

M1

N1

O1

P1

Q1

R1

S1

1

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xviii APPENDIX 3 SPSS DATA INPUT SHEETS (CONT’D) (WASTE CONTROL EVENTS) A2

B2

C2

D2

E2

F2

G2

H2

I2

J2

K2

L2

M2

N2

O2

P2

Q2

R2

S2

2

2

2

2

1

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2

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2

1

1

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1

1

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1

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1

1

1

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2

2

2

2

2

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

2

2

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2

2

2

2

2

2

2

2

2

2

2

2

1

1

2

2

2

2

1

2

2

1

2

2

2

2

1

2

2

2

2

2

2

2

2

2

2

2

2

2

2

xix APPENDIX 3 SPSS DATA INPUT SHEETS (CONT’D) (FREQUENCIES OF OCCURRENCES) A3

B3

C3

D3

E3

F3

G3

H3

I3

J3

K3

L3

M3

N3

O3

P3

Q3

R3

S3

3

3

3

2

5

4

4

4

4

3

4

4

3

3

3

3

3

2

4

3

3

2

2

4

3

3

2

4

2

2

3

4

4

3

5

4

3

2

3

3

4

3

4

3

3

3

3

3

3

3

3

3

3

4

4

4

2

4

3

3

3

4

3

4

4

4

4

4

3

4

4

3

5

4

3

3

4

3

4

3

3

3

3

3

3

2

2

2

3

3

2

3

3

4

2

4

4

4

3

3

3

4

3

3

4

4

4

4

4

5

5

5

3

3

3

1

2

1

4

1

2

2

2

4

4

5

4

3

2

5

5

2

3

2

2

2

1

2

3

3

2

1

1

2

2

2

2

2

4

4

2

1

4

3

3

3

3

2

2

2

2

3

3

2

3

3

3

4

3

3

2

3

4

2

3

4

3

4

3

2

4

3

3

3

4

2

4

3

3

3

5

4

5

3

3

3

3

2

4

3

4

3

4

2

2

3

4

3

3

5

3

3

4

4

3

3

1

3

2

2

2

3

3

3

5

5

4

2

3

3

4

4

4

3

3

2

3

3

3

2

3

2

3

3

3

3

3

4

2

3

2

5

2

4

2

4

3

5

5

5

5

3

2

2

4

3

4

4

4

3

5

3

3

3

3

4

3

4

4

4

5

5

4

5

3

4

5

5

4

4

1

2

2

3

3

3

2

3

3

4

5

5

5

2

3

3

2

2

3

1

1

1

1

2

2

2

4

4

3

4

4

1

2

4

4

4

2

4

1

2

1

3

3

3

3

3

3

2

4

3

4

3

4

3

3

3

3

3

3

4

3

4

4

3

4

4

3

4

4

3

3

3

4

4

4

5

2

2

3

5

3

3

3

4

4

3

5

4

3

3

4

4

4

4

4

3

4

2

4

3

3

3

3

4

2

4

3

4

3

4

3

2

1

3

1

3

2

2

3

3

3

2

3

3

4

4

4

1

3

4

5

3

4

3

2

2

2

4

3

4

4

3

4

3

4

4

2

4

2

3

2

3

2

3

2

3

2

1

2

3

3

4

4

3

3

3

4

2

3

2

5

3

2

2

4

3

3

3

3

3

2

3

4

3

2

3

3

3

2

4

2

3

3

3

4

4

4

3

3

3

4

4

2

2

5

3

3

3

4

2

4

3

3

4

4

3

3

4

3

4

4

4

3

xx APPENDIX 3 SPSS DATA INPUT SHEETS (CONT’D) (SCORE AGGREGRATION) D_WASTE1

D_WASTE2 D_WASTE3 NON_CON1 NON_CON2 NON_CON3

CON1

CON2

CON3

18.00

15.00

26.00

11.00

13.00

23.00

5.00

4.00

8.00

17.00

15.00

33.00

13.00

14.00

24.00

3.00

6.00

12.00

17.00

16.00

29.00

9.00

14.00

21.00

3.00

6.00

12.00

18.00

16.00

24.00

11.00

13.00

24.00

3.00

6.00

12.00

14.00

15.00

16.00

13.00

14.00

20.00

3.00

6.00

10.00

18.00

-

28.00

13.00

-

27.00

3.00

-

13.00

17.00

14.00

29.00

12.00

13.00

25.00

3.00

6.00

12.00

12.00

18.00

25.00

12.00

14.00

27.00

3.00

6.00

10.00

15.00

18.00

30.00

13.00

14.00

24.00

3.00

6.00

10.00

12.00

13.00

34.00

9.00

12.00

22.00

4.00

3.00

10.00

18.00

13.00

25.00

13.00

12.00

21.00

4.00

6.00

10.00

17.00

16.00

23.00

13.00

11.00

22.00

3.00

6.00

14.00

16.00

16.00

32.00

10.00

11.00

27.00

3.00

6.00

9.00

18.00

10.00

26.00

13.00

8.00

17.00

3.00

6.00

8.00

16.00

16.00

17.00

12.00

12.00

13.00

3.00

6.00

14.00

18.00

17.00

21.00

14.00

14.00

22.00

4.00

6.00

15.00

18.00

18.00

27.00

9.00

14.00

26.00

4.00

6.00

9.00

18.00

15.00

21.00

12.00

13.00

25.00

3.00

5.00

11.00

16.00

17.00

33.00

13.00

13.00

24.00

3.00

6.00

11.00

18.00

16.00

30.00

11.00

14.00

29.00

3.00

6.00

12.00

16.00

17.00

21.00

10.00

11.00

29.00

3.00

6.00

11.00

16.00

18.00

22.00

13.00

13.00

23.00

4.00

5.00

12.00

18.00

12.00

31.00

9.00

12.00

23.00

5.00

5.00

11.00

17.00

13.00

21.00

13.00

12.00

18.00

3.00

6.00

10.00

17.00

15.00

21.00

13.00

12.00

21.00

4.00

6.00

10.00

15.00

15.00

25.00

12.00

14.00

21.00

3.00

5.00

10.00

17.00

18.00

28.00

12.00

13.00

21.00

3.00

6.00

12.00

xxi APPENDIX 3 SPSS DATA INPUT SHEETS (CONT’D) (WASTE SOURCES/ CAUSES) A4_1 A4_2 A4_3 A4_4 B4_1 B4_2 B4_3 B4_4 B4_5 B4_6 C4_1 C4_2 C4_3 C4_4 C4_5 C4_6 D4_1 D4_2 D4_3 D4_4 D4_5 D4_6 E4_1 E4_2 E4_3 4

4

4

3

3

3

4

3

3

3

3

3

3

3

3

4

3

3

4

4

4

3

3

2

3

3

4

4

2

2

3

2

2

2

3

3

2

2

3

3

3

3

3

2

2

2

3

2

4

3

3

3

3

3

2

2

2

2

2

2

3

2

3

3

2

2

4

3

2

2

2

2

3

3

3

4

3

3

2

3

4

3

2

2

2

2

3

3

3

2

3

2

2

3

2

3

2

3

4

3

3

3

2

2

3

3

3

3

4

2

2

4

3

3

3

3

4

4

4

2

1

2

2

4

4

2

2

2

2

3

3

2

3

3

2

2

3

2

2

2

3

3

3

3

2

3

3

3

3

3

3

4

3

2

2

3

3

2

3

3

2

2

3

3

2

2

3

3

2

4

2

2

3

3

3

4

3

3

3

3

3

3

3

4

4

1

1

3

2

4

3

4

4

3

4

4

4

3

4

4

3

3

3

3

3

3

4

3

3

2

2

2

3

3

3

3

2

3

3

3

3

3

3

4

3

3

3

3

3

4

3

3

3

3

3

3

3

4

3

3

3

3

3

3

3

3

3

3

3

3

4

4

-

4

4

4

3

4

2

3

3

2

2

2

2

2

4

4

4

4

4

4

4

4

4

4

4

4

3

4

3

3

4

4

3

4

4

4

4

4

3

4

4

3

3

3

3

4

4

3

3

3

3

4

3

4

4

3

3

2

3

2

3

2

3

3

3

4

4

3

3

3

4

4

4

4

4

4

3

3

4

4

3

4

4

4

4

4

4

4

3

4

4

4

4

3

4

4

4

4

4

3

3

3

3

3

4

3

3

3

3

2

3

3

3

3

3

4

4

4

3

3

3

4

3

4

4

4

3

3

3

3

4

4

3

2

2

3

3

3

3

4

4

4

4

4

4

4

4

3

2

2

4

2

2

3

3

3

3

2

3

2

2

2

2

2

2

2

3

3

3

3

3

3

2

4

3

3

3

3

2

2

3

2

3

2

3

3

3

3

4

3

4

4

3

3

4

3

4

4

4

3

3

3

3

3

3

3

3

3

3

3

2

3

4

3

3

4

4

3

3

4

3

4

3

3

3

4

2

3

3

3

2

3

3

3

3

3

3

3

3

4

3

3

4

4

4

4

4

3

4

4

4

3

4

4

3

3

4

3

4

3

3

3

3

4

3

4

4

4

3

3

3

4

4

3

3

3

3

3

3

3

4

3

3

3

3

3

3

3

3

3

3

4

2

2

3

3

4

3

3

4

3

3

3

3

3

3

2

3

2

2

4

3

3

2

3

4

3

3

3

3

3

3

4

3

3

3

2

2

3

3

3

2

3

2

2

2

3

3

2

4

3

3

4

2

2

3

4

3

3

3

3

3

3

3

3

2

3

1

3

3

3

2

2

3

3

3

3

3

3

3

3

3

3

4

3

3

3

2

3

3

3

3

3

2

1

3

2

2

3

4

3

3

3

3

3

3

4

3

3

3

3

3

3

3

3

3

3

2

3

2

3

3

3

3

2

3

2

2

3

3

3

3

3

xxii APPENDIX 4 CAUSES AND EFFECTS MATRIX TABLES

MAJOR CAUSE

A B C D E F G H I J K L M N O P Q R

A1 A2 A3 A4 B1 8 7 5 12 3 8 3 1 5 5 5 8 3 2 5 5 10 4 9 5 4 6 4 4 1 1 1 1 2 2 2 2 1 1 5 1 1 1 4 2 3 1 3 7 1 3 1 5 1

B2 B3 B4 B5 B6 C1 C2 C3 C4 C5 C6 D1 D2 D3 D4 D5 D6 E1 E2 E3 F 2 1 3 1 2 1 4 5 1 1 1 1 2 1 1 7 1 3 2 2 1 2 3 1 1 7 2 1 1 1 11 3 1 1 1 1 2 1 9 3 3 2 2 2 1 4 3 3 2 2 1 2 4 2 1 7 5 9 6 1 4 5 1 1 1 3 1 4 1 1 3 2 2 1 1 1 1 1 2

xxiii APPENDIX 4 CAUSES AND EFFECTS MATRIX TABLES (CONT’D) OTHER CAUSES

A B C D E F G H I J K L M N O P Q R

A1 3 4 5 5 1 2 2 3

1

1 1 1

A2 5 1 2 3 1 2 1 1 1

A3 A4 B1 B2 B3 B4 B5 5 1 1 1 2 1 1 3 1 2 3 1 1 2 1 3 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 3 3 1 3 1 1 1 1 1 1 1 2 1 2 3 2 1 1 2 1 1 1 3 1 2 1

B6 C1 C2 C3 1 1 1 3 1 4 1 1 1 1 5 2 2 2 1

C4 C5 C6 D1 D2 D3 D4 D5 D6 E1 1 1 1 2 1 2 3 1 1 1 1 2 5 2 1 4 1 1

1 1 2

1

4 1

1

2

1

2 3 2 1

1 1

2 1 1 2

1

1

E2 E3 F 3 1 1 1 1 2 5 6 1 1 1 1

1 1 3

2

1

1

1 2

1 2

1

3

1 1 1 1

1 1

3 3 1

3 3 1

3 4

1

1

1 1

2 1

2

1

1

1

1 1

xxiv APPENDIX 5 SAMPLE OF QUESTIONNAIRE Construction Wastes Study Based on Lean Construction This study is focused on the study of wastes concepts based on Lean Construction Philosophy in local construction industry. The questionnaire will consist of 4 sections, which intend to study: 1) The general perception and acceptance of Lean Construction philosophy and the waste concepts by local construction industry 2) The extent of waste problems in existing local industry 3) The relevant sources of wastes to have significant impacts on project 4) And finally to create correlation matrix between wastes and the sources of wastes Background Information A. Please indicate your position in the project organisation Position q

Project Manager

q

Project Scheduler/ Planner

q

Resident Engineer

q

Foreman

q

Site Engineer

q

q

Site Supervisor

Other (Please specify): ______________________

B. Please select the most appropriate type of construction project to describe the area of projects most frequently involved by your company: q

High rise building

q

q

Residential & commercial scheme

q

q

Industrial projects

q

Public & community buildings

Civil & road construction Others ( Please specify): _____________________

C. Please indicate the CIDB registration grade: q

Below Grade 3

q

Grade 3 and above

D. Please select the most project clients related to the projects carried out: q

Private

q

Public

xv Section A: General Perception 1. To your experience and opinion, which are the following items or activities can be best represented or described as “Waste” or “Non Value Added” to Construction site: (Please indicate X in the Waste column for waste activities and Non-Waste column for non-waste activities) Waste A.

Waiting for others to complete their works before the proceeding works can be carried out

B.

Waiting for equipment to be delivered on site

C.

Waiting for materials to be delivered on site

D.

Waiting for the skilled workers to be on site

E.

Waiting for the clarification and confirmation by client and consultants

F.

Over-allocation/ unnecessary equipment on site

G.

Over-allocation/ unnecessary materials on site

H.

Over-allocation/ unnecessary workers on site

I.

Unnecessary procedures and working protocols

J.

Material loss/ stolen from site during construction periods

K.

Material deterioration/ damaged during construction periods

L.

Mishandling or error in construction applications/ installation M. Time for rework/ repair works/ defective works N.

Materials for rework/ repair works/ defective works

O.

Time for workers’ resting during construction

P.

Time in supervising and inspecting the construction works

Q.

Time for instructions and communication among different tiers and trades of workers

R.

Time for transporting workers, equipment and materials

S.

Accidents on site

Non-Waste

xvi Section B: Existing Scenario and Practice in The Local Industry 2. To your experience in your work field, is any of the following events are properly controlling and mitigated in the construction site. (Please indicate X in the Yes column for controlled events and No column for uncontrolled events) Yes A.

Waiting for others to complete their works before the proceeding works can be carried out

B.

Waiting for equipment to be delivered on site

C.

Waiting for materials to be delivered on site

D.

Waiting for the skilled workers to be on site

E.

Waiting for the clarification and confirmation by client and consultants

F.

Over-allocation/ unnecessary equipment on site

G.

Over-allocation/ unnecessary materials on site

H.

Over-allocation/ unnecessary workers on site

I.

Unnecessary procedures and working protocols

J.

Material loss/ stolen from site during construction periods

K.

Material deterioration/ damaged during construction periods

L.

Mishandling or error in construction applications/ installation

M. Time for rework/ repair works/ defective works N.

Materials for rework/ repair works/ defective works

O.

Time for workers’ resting during construction

P.

Time in supervising and inspecting the construction works

Q.

Time for instructions and communication among different tiers and trades of workers

R.

Time for transporting workers, equipment and materials

S.

Accidents on site

No

xvii 3. To your experience in your work field, what is the frequency of occurrence of the mentioned activities on construction site Please indicate the frequency of occurrence of the mentioned activities by using the scale of 1 to 5. (1 = Never, 5 = Very Frequent). 1

2

3

4

5

Never

Very Rare

Seldom

Frequent

Very Frequent

A.

Waiting for others to complete their works before the proceeding works can be carried out

B.

Waiting for equipment to be delivered on site

C.

Waiting for materials to be delivered on site

D.

Waiting for the skilled workers to be on site

E.

Waiting for the clarification and confirmation by client and consultants

F.

Over-allocation/ unnecessary equipment on site

G.

Over-allocation/ unnecessary materials on site

H.

Over-allocation/ unnecessary workers on site

I.

Unnecessary procedures and working protocols

J.

Material loss/ stolen from site during construction periods

K.

Material deterioration/ damaged during construction periods

L.

Mishandling or error in construction applications/ installation

M.

Time for rework/ repair works/ defective works

N.

Materials for rework/ repair works/ defective works

O.

Time for workers’ resting during construction

P.

Time in supervising and inspecting the construction works

Q.

Time for instructions and communication among different tiers and trades of workers

R.

Time for transporting workers, equipment and materials

S.

Accidents on site

xviii

Section C: Sources/ Causes of Wastes 4. To your opinion, please identify the most likely sources/ causes of wastes to impact on the productivity of the projects Please indicate the frequency of occurrence of the mentioned activities by using the scale of 1 to 5. (1 = Most Unlikely, 4 = Most Likely). 1

2

3

4

Most Unlikely

Unlikely

Likely

Most Likely

Management & Administration Factors A1

Poor coordination among project participants

A2

Poor planning and scheduling

A3

Lack of control

A4

Bureaucracy

People Factors B1 Lack of trades skills B2

Inexperience inspectors

B3

Too few supervisors/ foreman

B4

Uncontrolled sub-contracting practices

B5

Supervision too late

B6

Poor labour distribution

Execution Factors C1 Inappropriate construction methods C2

Outdated equipment

C3

Equipment shortage

C4

Poor equipment choice or ineffective equipment

C5

Poor site layout and setting out

C6

Poor site documentation

xix Material Factors D1 Delay of material delivery D2

Poorly scheduled delivery of material to site

D3

Poor quality of material

D4

Inappropriate/ misuse of material

D5

Poor storage of material

D6

Poor material handling on site

Information and Communication Factors E1 Defective or Wrong information E2

Late information and decision making

E3

Unclear information

xx Section D: Cause and Effects Relationship 5. To your experience in your work field, please relate the waste variations to the contributory sources of wastes. (Please fill in other secondary causes [if any] in the Other Causes Column, the causes can be either from the list below or whichever causes differ from the list [Please specify]) A1

Poor coordination among project participants

A2

Poor planning and scheduling

A3

Lack of control

A4

Bureaucracy

C1

Inappropriate construction methods

C2

Outdated equipment

C3

Equipment shortage

C4

Poor equipment choice or ineffective equipment

C5

Poor site layout and setting out

C6

Poor site documentation

B1

Lack of trades skills

B2

Inexperience inspectors

B3

Too few supervisors/ foreman

B4

Uncontrolled sub-contracting practices

D1

Delay of material delivery

B5

Supervision too late

D2

Poorly scheduled delivery of material to site

B6

Poor labour distribution D3

Poor quality of material

Example:

D4

Inappropriate/ misuse of material

For A: Waiting for others to complete their works before proceeding works can be carried out

D5

Poor storage of material

D6

Poor material handling on site

E1

Defective or wrong information

E2

Late information and decision making

E3

Unclear information

F

Not relevant

Major cause column can be filled with one major cause to the problem for example A2: poor planning & scheduling Other cause can be filled with more than 1 cause for example A3, A4 & B5 and so on.

xxi

Events A

Waiting for others to complete their works before the proceeding works can be carried out

B

Waiting for equipment to be delivered on site

C

Waiting for materials to be delivered on site

D

Waiting for the skilled workers to be on site

E

Waiting for the clarification and confirmation by client/ consultants

F

Over-allocation/ unnecessary equipment on site

G

Over-allocation/ unnecessary materials on site

H

Over-allocation/ unnecessary workers on site

I

Unnecessary procedures and working protocols

J

Material loss/ stolen from site during construction periods

K

Material deterioration/ damaged during construction periods

L

Mishandling or error in construction applications/ installation

M

Rework/ repair works/ defective works

N

Workers’ resting during construction

O

Supervising and inspecting the construction works

P

Instructions and communication among different tiers and trades of workers

Q

Transporting workers, equipment and materials

R

Accidents on site

Major Cause

Other Causes