Waste Reduction in Precast Construction: Using Lean and Shared Mental Models [1st ed.] 9789811587986, 9789811587993

This book presents the adaptation of lean principles to the precast construction industry to eliminate or minimize const

262 30 5MB

English Pages XVI, 250 [255] Year 2021

Report DMCA / Copyright

DOWNLOAD PDF FILE

Table of contents :
Front Matter ....Pages i-xvi
Introduction (Joy Ong, Low Sui Pheng)....Pages 1-11
Construction Productivity in Singapore (Joy Ong, Low Sui Pheng)....Pages 13-20
Precast Construction (Joy Ong, Low Sui Pheng)....Pages 21-43
Lean Construction Implementation (Joy Ong, Low Sui Pheng)....Pages 45-74
Shared Mental Models Development (Joy Ong, Low Sui Pheng)....Pages 75-88
Research Design and Methodology (Joy Ong, Low Sui Pheng)....Pages 89-97
Results and Analysis (Joy Ong, Low Sui Pheng)....Pages 99-140
Case Study (Joy Ong, Low Sui Pheng)....Pages 141-156
Conclusion and Recommendations (Joy Ong, Low Sui Pheng)....Pages 157-163
Back Matter ....Pages 165-250
Recommend Papers

Waste Reduction in Precast Construction: Using Lean and Shared Mental Models [1st ed.]
 9789811587986, 9789811587993

  • 0 0 0
  • Like this paper and download? You can publish your own PDF file online for free in a few minutes! Sign Up
File loading please wait...
Citation preview

Management in the Built Environment Series Editor: Low Sui Pheng

Joy Ong Low Sui Pheng

Waste Reduction in Precast Construction Using Lean and Shared Mental Models

Management in the Built Environment Series Editor Low Sui Pheng, National University of Singapore, Singapore, Singapore Editorial Board Abdul Rashid Bin Abdul Aziz, University Science Malaysia, Penang, Malaysia An Min, Salford University, Salford, UK Azlan Shah Ali, Faculty of Built Environment, University of Malaya, Department of Building Surveying, Kuala Lumpur, Malaysia Faisal M. Arain, Niagara College, Makkah Campus, Welland, ON, Canada Fang Dongping, Tsinghua University, Beijing, China Gao Shang, University of Melbourne, Parkville, VIC, Australia George Ofori, London South Bank University, London, UK Hamzah A. Rahman, University of Malaya, Kuala Lumpur, Malaysia Javier Cuervo, Department of Management and Marketing, University of Macau, Taipa, Macau, Guangdong, China Liu Junying, Department of Construction Management, Tianjin University, Nankai, Tianjin, China Oluwayomi K. Babatunde, Construction Economics & Management, University of the Witwatersrand, Johannesburg, Gauteng, South Africa Oswald Chong, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA

The aim of this book series is to provide a platform to build and consolidate a rigorous and significant repository of academic, practice and research publications that contribute to further knowledge relating to management in the built environment. Its objectives are to: 1. Disseminate new and contemporary knowledge relating to research and practice in the built environment 2. Promote synergy across different research and practice domains in the built environment and 3. Advance cutting-edge research and best practice in the built environment The scope of this book series is not limited to “management” issues per se because this then begs the question of what exactly are we managing in the built environment. While the primary focus is on management issues in the building and construction industry, its scope has been extended upstream to the design management phase and downstream to the post-occupancy facilities management phase. Management in the built environment also involves other closely allied disciplines in the areas of economics, environment, legal and technology. Hence, the starting point of this book series lies with project management, extends into construction and ends with facilities management. In between this spectrum, there are also other management-related issues that are allied with or relevant to the built environment. These can include, for example cost management, disaster management, contract management and management of technology. This book series serves to engage and encourage the generation of new knowledge in these areas and to offer a publishing platform within which different strands of management in the built environment can be positioned to promote synergistic collaboration at their interfaces. This book series also provides a platform for other authors to benchmark their thoughts to identify innovative ideas that they can further build on to further advance cutting-edge research and best practice in the built environment. If you are interested in submitting a proposal for this series, please kindly contact the Series Editor or the Publishing Editor at Springer: Low Sui Pheng ([email protected]) or Ramesh Premnath ([email protected])

More information about this series at http://www.springer.com/series/15765

Joy Ong Low Sui Pheng •

Waste Reduction in Precast Construction Using Lean and Shared Mental Models

123

Joy Ong Department of Building National University of Singapore Singapore, Singapore

Low Sui Pheng Department of Building National University of Singapore Singapore, Singapore

ISSN 2522-0047 ISSN 2522-0055 (electronic) Management in the Built Environment ISBN 978-981-15-8798-6 ISBN 978-981-15-8799-3 (eBook) https://doi.org/10.1007/978-981-15-8799-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Despite efforts in recent years, construction remains the most inefficient industry in many countries. Lean principles have brought about massive productivity growth in the manufacturing industry but application to the construction industry is still relatively unknown or unexplored. From a lean point of view, poor construction productivity is due to construction wastes, that is, defects and rework, overproduction, waiting and idle time, non-utilised resources, transportation, inventory, motion and extra-processing. One of the key movements in the Singapore construction industry is the adoption of precast construction which involves transforming construction into a manufacturing process with more off-site prefabrication to improve site productivity. Yet contractors are still encountering high occurrence of construction wastes and the pool of foreign workers have not reduced significantly. This calls for more theoretical research to understand the value of enabling lean in precast construction. To eliminate or minimise construction wastes, lean construction was adopted to model the precast construction process influencing manpower requirements. This is done using the shared mental models theory to understand how the lean principles enable people to work together to complete the tasks and work together effectively as a team throughout the entire precast construction process from the design, production, logistics to installation stages. Shared mental models is essentially the convergence among team members’ mental representations regarding various aspects of their team and tasks. The greater the commonality of their mental models, the greater the likelihood of the team’s ability to perform effectively. Teams who share mental models can understand other members’ roles and knowledge and become more effective to deliver successful outcomes. Besides the theoretical concepts, this study also presents the practical aspects faced by contractors through the conduct of questionnaire surveys to understand how the implementation of lean principles and shared mental models will affect the occurrence of construction wastes and hence the changes in the total man-days used during the precast construction process. These were further anchored by in-depth interviews with industry practitioners in the Singapore construction industry to validate the survey results. v

vi

Preface

Collectively, the empirical findings collated from the building professionals suggest that a lean-enabled precast construction project leads to reduction in the occurrence of construction wastes and reduction in the total man-days used, both on-site and off-site, and the extent of reduction varies according to the different extent of lean construction implementation. The added effect of developing shared mental models among the team members is shown to further reduce the occurrence of construction wastes and result in better productivity performance. Hence, this study suggests that contractors should be integrating lean construction considerations with shared mental models development into the precast construction process to influence the impact on construction productivity in terms of the total manpower required. This study also proposed a neural network model for developing leading indicators that classify precast construction projects in accordance with the manpower changes achieved with the reduction of the occurrence of construction wastes. A case study was conducted and the results validated that the model would allow contractors to predict the risk of low construction productivity at an early stage and enable them to proactively take actions to further optimise the total man-days to be utilised in the subsequent precast construction stages. This study has contributed to the extant literature, shedding light on enabling lean through using shared mental models for precast construction in Singapore. A different approach is taken by assessing how team members involved in a precast construction project work together to minimise wastage of materials, time and effort throughout the precast construction process. This is distinct from the present site productivity measurement which focuses on the workers on-site. The construction industry will also benefit with contractors giving more attention to further develop their team’s shared mental models and implementation of lean construction principles to reduce the total man-day utilisation in their projects. Overall, this study has drawn an important practical implication with true accounts and reflections of real-life practices and experiences to help contractors to identify which areas to focus on throughout the entire precast construction process from the design, production, logistics to installation stages to further improve the rate of construction productivity. Singapore

Joy Ong Low Sui Pheng

Contents

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

1 1 3 5 6 7 9 9 9

2 Construction Productivity in Singapore . 2.1 Overview . . . . . . . . . . . . . . . . . . . . . 2.2 Productivity Measurement and Trend . 2.3 Manpower Requirements . . . . . . . . . . 2.4 Technology Adoption . . . . . . . . . . . . 2.5 Gaps in Current Research . . . . . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

13 13 13 17 19 20

3 Precast Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Design for Manufacturing and Assembly . . . . . . . . . . . . . . 3.3 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Prefabricated Prefinished Volumetric Construction . 3.3.2 Prefabricated Volumetric Construction . . . . . . . . . . 3.3.3 In-Built Bathroom . . . . . . . . . . . . . . . . . . . . . . . . 3.3.4 Advanced Prefabricated Systems and Prefabricated Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

21 21 22 23 23 26 27

.....

27

1 Introduction . . . . . . . . . . . . . . . . . . 1.1 Background . . . . . . . . . . . . . . . 1.2 Research Problem and Question 1.3 Research Aim and Objectives . . 1.4 Research Scope . . . . . . . . . . . . 1.5 Research Methodologies . . . . . . 1.6 Research Significance . . . . . . . . 1.7 Research Hypotheses . . . . . . . . 1.8 Book Structure . . . . . . . . . . . . .

. . . . . . . . .

. . . . . . . . .

. . . . . . . . .

vii

viii

Contents

3.4 Stakeholders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Considerations During the Process of Precast Construction 3.5.1 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.2 Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.3 Logistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.4 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Gaps in Current Research . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

28 28 29 32 35 37 40

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . .

45 45 45 49 49 51 51 52 52 53 54 62 62 63 63 64 64 64 65 65 65 66

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

. . . . .

66 67 67 67 68

............. ............. .............

75 75 75

4 Lean Construction Implementation . . . . . . . . . . . . . . 4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 The Toyota Story . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Applying Lean in Streamlining Manpower . . . . . . 4.3.1 Just-in-Time . . . . . . . . . . . . . . . . . . . . . 4.3.2 Levelled Production . . . . . . . . . . . . . . . . 4.3.3 Jidoka . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Visual Management . . . . . . . . . . . . . . . . 4.3.5 Stable and Standardised Process . . . . . . . 4.3.6 Continuous Improvement . . . . . . . . . . . . 4.4 Lean Production to Lean Construction . . . . . . . . . 4.5 Precast Construction Process Shift Through Lean . 4.5.1 Focus on Long-Term Results . . . . . . . . . 4.5.2 Create One-Piece Flow . . . . . . . . . . . . . . 4.5.3 Use Pull-Replenishment . . . . . . . . . . . . . 4.5.4 Level Out the Workload . . . . . . . . . . . . . 4.5.5 Stop to Fix Problems . . . . . . . . . . . . . . . 4.5.6 Standardise Tasks . . . . . . . . . . . . . . . . . 4.5.7 Visualise Process . . . . . . . . . . . . . . . . . . 4.5.8 Adapt to Operations . . . . . . . . . . . . . . . . 4.5.9 Empower Your People . . . . . . . . . . . . . . 4.5.10 Develop Your People . . . . . . . . . . . . . . . 4.5.11 Grow Together with Solid Subcontractors and Suppliers . . . . . . . . . . . . . . . . . . . . . 4.5.12 Observe and Understand the Process . . . . 4.5.13 Consider Alternative Solutions . . . . . . . . 4.5.14 Review Process . . . . . . . . . . . . . . . . . . . 4.6 Gaps in Current Research . . . . . . . . . . . . . . . . . . 5 Shared Mental Models Development . . . . . . . . . . . . 5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Shared Mental Models Theory . . . . . . . . . . . . . 5.3 Underpinning Lean Construction Implementation Construction . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . .

in Precast .............

79

Contents

ix

5.3.1 Design Stage . . . . . 5.3.2 Production Stage . . 5.3.3 Logistics Stage . . . 5.3.4 Installation Stage . . 5.4 Summary . . . . . . . . . . . . . . 5.5 Proposed Conceptual Model

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

. . . . . .

79 80 81 81 82 83

6 Research Design and Methodology 6.1 Research Design . . . . . . . . . . . 6.2 Data Collection Method . . . . . 6.3 Data Analysis Method . . . . . . 6.3.1 Overview . . . . . . . . . . 6.3.2 Hypotheses Testing . . 6.3.3 Neural Network . . . . . 6.4 Validation . . . . . . . . . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

89 89 90 93 93 93 94 96

7 Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Overview of Research Analysis . . . . . . . . . . . . . . . . . . . . . . . 7.2 Analysis of Respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Analysis of Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Data Understanding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.1 Lean Principles and Shared Mental Models . . . . . . . . 7.4.2 Changes in Man-Days . . . . . . . . . . . . . . . . . . . . . . . 7.4.3 Strength of Dependence Between Reduction of Construction Wastes and Manpower Changes . . . . 7.5 Data Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.1 Leading Indicator of Precast Productivity Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.2 Relationship Between Reduction of Construction Wastes and Leading Indicator of Precast Productivity Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.1 Neural Network Structure . . . . . . . . . . . . . . . . . . . . . 7.6.2 Independent Variable Importance Analysis . . . . . . . . 7.6.3 Classification Results . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

99 99 99 103 111 111 115

. . . . . .

. . . . . .

. . . . . .

124 127 127 128 132 135

8 Case Study . . . . 8.1 Overview . . 8.2 Background 8.3 Findings . . . 8.4 Discussion . 8.5 Validation . 8.6 Conclusion .

. . . . . . .

. . . . . . .

. . . . . . .

141 141 141 143 144 147 147

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . . . . .

. . . 117 . . . 122 . . . 122

x

9 Conclusion and Recommendations . . . . . . . . . . . . 9.1 Discussion of Main Findings . . . . . . . . . . . . . . 9.2 Concluding the Hypotheses . . . . . . . . . . . . . . . 9.3 Contributions to Knowledge and Practice . . . . . 9.4 Limitations of Study and Recommendations for Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . .

Contents

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

157 157 159 159

Future . . . . . . . . . . . . . . 162 . . . . . . . . . . . . . . 163

Appendix A: Details of Industry Practitioners . . . . . . . . . . . . . . . . . . . . . 165 Appendix B: Pilot Survey Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Appendix C: Final Survey Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . 183 Appendix D: Guiding Questions Used For Interviews . . . . . . . . . . . . . . . 203 Appendix E: Verbatim Report With Mr. A . . . . . . . . . . . . . . . . . . . . . . . 205 Appendix F: Verbatim Report With Mr. B . . . . . . . . . . . . . . . . . . . . . . . 211 Appendix G: Verbatim Report With Mr. C . . . . . . . . . . . . . . . . . . . . . . . 217 Appendix H: Verbatim Report With Mr. D . . . . . . . . . . . . . . . . . . . . . . . 223 Appendix I: Verbatim Report With Mr. E . . . . . . . . . . . . . . . . . . . . . . . . 227 Appendix J: Verbatim Report With Mr. F . . . . . . . . . . . . . . . . . . . . . . . . 233 Appendix K: Verbatim Report For Case Study . . . . . . . . . . . . . . . . . . . . 237 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241

Abbreviations

2D 3D ALC AUC BCa BCA BIM BIP C21 CITM CONQUAS CS CW01 DB DBB DFA DFM DfMA ECI FCWDS Ford GFA HDB ICT ICPH IPA ISO JIT M&E MEP

Two-Dimensional Three-Dimensional Autoclaved Lightweight Concrete Area Under the Curve Bias Corrected and Accelerated Building and Construction Authority Building Information Modelling Building Innovation Panel Construction 21 Construction Industry Transformation Map Construction Quality Assessment System Constructability Score Construction Workhead for General Building Design-and-Build Design-Bid-Build Design for Assembly Design for Manufacture Design for Manufacturing and Assembly Early Contractor Involvement Foreign Construction Worker Directory System Ford Motor Company Gross Floor Area Housing and Development Board Info-Communications Technology Integrated Construction and Prefabrication Hubs In-Principal Acceptance International Organisation for Standardisation Just-In-Time Mechanical and Electrical Mechanical, Electrical, and Plumbing

xi

xii

MOM MTI NPQS PBU PDCA PMETs PPVC QCC QP R&D ROC SCAL TA(C) TFP TPS TQM UK US VDC WD(C)

Abbreviations

Ministry of Manpower Ministry of Trade and Industry National Productivity and Quality Specifications Prefabricated Bathroom Unit Plan-Do-Check-Act Professionals, Managers, Executives, and Technicians Prefabricated Prefinished Volumetric Construction Quality Control Circle Qualified Persons Research and Development Receiver Operating Characteristic Singapore Contractors Association Ltd Technology Adoption (Construction) Total Factor Productivity Toyota Production System Total Quality Management United Kingdom United States Virtual Design and Construction Workforce Development (Construction)

List of Figures

Fig. 1.1 Fig. 1.2 Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 3.1 Fig. 3.2 Fig. Fig. Fig. Fig.

4.1 4.2 5.1 5.2

Fig. Fig. Fig. Fig. Fig. Fig. Fig.

5.3 6.1 7.1 7.2 7.3 7.4 7.5

Fig. 7.6

Fig. 7.7 Fig. 7.8 Fig. 7.9

Team members from main contractor and precaster . . . . . . . . Research methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Annual percentage change in value added per worker. (Source BCA 2017b) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cumulative site productivity growth. (Source BCA 2019a) . . Employed foreign and resident workers in the construction industry. (Source MOM 2019; MTI 2019) . . . . . . . . . . . . . . . Comparison between DBB and DB with ECI . . . . . . . . . . . . . Construction Productivity and Capability Fund schemes. (Source BCA 2017c) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The TPS house. (Source Gao and Low 2014) . . . . . . . . . . . . . Toyota way model. (Source Liker and Meier 2006) . . . . . . . . Conception of shared mental models . . . . . . . . . . . . . . . . . . . Working together from end-to-end in a lean manner for precast construction capability development . . . . . . . . . . . . . . . . . . . . Proposed conceptual model . . . . . . . . . . . . . . . . . . . . . . . . . . . Overall research design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overall structure of research analysis process . . . . . . . . . . . . . Response rate of each team member . . . . . . . . . . . . . . . . . . . . Respondent breakdown by company’s tendering limit . . . . . . Average years of experience of each team member . . . . . . . . Boxplot of leading indicator of precast productivity performance against changes in the occurrence of construction wastes due to lean construction implementation . . . . . . . . . . . Boxplot of leading indicator of precast productivity performance against changes in the occurrence of construction wastes due to development of shared mental models . . . . . . . Boxplot of leading indicator of precast productivity performance against changes in the manpower utilisation . . . . Multi-layer perceptron network structure . . . . . . . . . . . . . . . . Predicted by observed boxplot . . . . . . . . . . . . . . . . . . . . . . . .

.. ..

6 8

.. ..

14 16

.. ..

18 29

. . . .

. . . .

34 50 55 79

. . . . . . .

. . . . . . .

87 88 90 101 101 102 102

. . 123

. . 123 . . 124 . . 129 . . 133 xiii

xiv

Fig. Fig. Fig. Fig.

List of Figures

7.10 7.11 7.12 8.1

Specificity versus sensitivity chart. . . . . . . . . . . . . . . . . . . . . . Cumulative gains chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lift chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prediction model for leading indicator of precast productivity performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . 134 . . 135 . . 136 . . 155

List of Tables

Table 1.1 Table 2.1 Table Table Table Table

2.2 3.1 3.2 3.3

Table 3.4 Table 4.1 Table 4.2 Table 4.3 Table 5.1 Table 5.2 Table 6.1 Table 6.2 Table 6.3 Table Table Table Table Table

6.4 7.1 7.2 7.3 7.4

Table 7.5

Research hypotheses formulation and purpose . . . . . . . . . . . Annual change in economic and physical productivity in the construction industry . . . . . . . . . . . . . . . . . . . . . . . . . Overall site productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . Classification of DfMA by disciplines . . . . . . . . . . . . . . . . . General scope of work for PPVC . . . . . . . . . . . . . . . . . . . . . Minimum level of finishing and fittings to be completed off-site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Construction wastes in precast construction incurring more manpower effort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Toyota way management principles . . . . . . . . . . . . . . . . . . . Proposed lean implementation in precast construction . . . . . Mapping of key construction wastes in precast construction and relevant lean principles for total man-day reduction . . . Proposed characteristics of shared mental models theory for precast construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis of enabling lean in precast construction using the lens of shared mental models theory . . . . . . . . . . . . . . . Criteria for population to be sampled . . . . . . . . . . . . . . . . . . Transforming Likert scale to range of percentages . . . . . . . . Number of post-survey interviews gathered from recent Doctoral’s theses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Details of interviewees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Purpose of research analysis . . . . . . . . . . . . . . . . . . . . . . . . Mean rank of each team member . . . . . . . . . . . . . . . . . . . . . Results of Kruskal–Wallis test . . . . . . . . . . . . . . . . . . . . . . . Descriptive statistics of attributes resulting in reduction in occurrence of construction wastes . . . . . . . . . . . . . . . . . . Convergent validity analysis of attributes resulting in reduction in occurrence of construction wastes . . . . . . . . . .

..

10

. . . .

. . . .

16 17 24 25

..

26

.. .. ..

40 56 69

..

71

..

77

.. .. ..

84 91 92

. . . . .

. 96 . 97 . 100 . 104 . 110

. . 112 . . 118

xv

xvi

List of Tables

Table 7.6 Table 7.7 Table 7.8 Table 7.9 Table 7.10 Table 7.11 Table Table Table Table Table Table

7.12 7.13 7.14 7.15 7.16 7.17

Table Table Table Table Table Table

8.1 8.2 8.3 8.4 8.5 9.1

Descriptive statistics of attributes resulting in changes in man-day used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Convergent validity analysis of attributes resulting in changes in manpower used . . . . . . . . . . . . . . . . . . . . . . . . . Spearman rank-order correlation coefficient tests for manpower changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Classification into leading indicator of precast productivity performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spearman rank correlation coefficient tests for leading indicator of precast productivity performance. . . . . . . . . . . . Concerns about the leading indicator for precast productivity performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neural network information . . . . . . . . . . . . . . . . . . . . . . . . . Synaptic weights of respective parameter estimates . . . . . . . Neural network model summary . . . . . . . . . . . . . . . . . . . . . Independent variable importance analysis. . . . . . . . . . . . . . . Classification results of using the neural network. . . . . . . . . Lean enablers reinforcing shared mental models in precast construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Background of projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparison of classification results . . . . . . . . . . . . . . . . . . . Validation approach and sensitivity analysis . . . . . . . . . . . . Matrix of on-site and off-site man-day for Project No. 1 . . . Matrix of on-site and off-site man-day for Project No. 2 . . . Review of hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . 115 . . 118 . . 119 . . 122 . . 126 . . . . . .

. . . . . .

127 128 130 131 131 132

. . . . . . .

. . . . . . .

137 142 143 148 154 154 160

Chapter 1

Introduction

1.1 Background Low construction productivity growth has been a global phenomenon for at least fifty years (Naoum 2016). Apart from developing countries, Australia, Canada, European countries, Japan, and United States (US) have for decades recorded declines or slowdown in measured labour productivity in construction (Fulford and Standing 2014; Nasir et al. 2014). The poor quality of staffs, inefficient management of resources, as well as weak levels of investment and innovation are some of the key factors affecting productivity in the construction industry (Hughes and Thorpe 2014). However, Singapore’s efforts to prompt radical change and accelerate productivity growth do not seem desirable despite strong support from the government. In 2010, Singapore set the target of 2–3% annual site productivity growth over the next ten years but the site productivity only increased by an average of 1.8% per year between 2010 and 2018 (BCA 2019a). Site productivity has been hard to raise in Singapore’s construction industry as she is heavily dependent on foreign workers to fulfil the construction demand. Hence, the construction industry is deeply concerned that the desired site productivity target will not be met and much catching up should be done in the remaining few years (MND 2015). Precast construction can significantly raise site productivity and it stems from the concept of Design for Manufacturing and Assembly (DfMA) which involves the design of building components for construction off-site to result in simple assembly on site. The Singapore’s construction industry started implementing the DfMA concept in the adoption of two-dimensional (2D) precast components for the construction of residential flats in the 1960s. This advanced to the three-dimensional (3D) Prefabricated Bathroom Unit (PBU) in 2000. This has contributed to site productivity gains for many residential projects in Singapore. In 2014, the DfMA concept expanded to the adoption of Prefabricated Prefinished Volumetric Construction (PPVC) in residential, hotels and institutional types of developments in Singapore (BCA 2019b). However, the emphasis on moving towards precast construction © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_1

1

2

1 Introduction

is simply about automating processes off-site such that the scope of prefabrication is not counted under site productivity. As at 1 August 2019, 28 precasters are accredited under the Singapore Concrete Institute’s Precaster Accreditation Scheme and there are five Integrated Construction and Prefabrication Hubs (ICPH) in Singapore. Of which three ICPH are in operation and two are undergoing construction. ICPH are multi-storey advanced manufacturing facilities for producing prefabricated construction components in an automated manner (BCA 2018). Each ICPH is only about two hectares and on a 30-year lease term which is relatively small and short for producing the large precast components to make economic sense. Due to land constraints and cost considerations, the main source of precast concrete in Singapore still comes from Malaysia. This means that majority of the contractors are relying on factories and manpower overseas to supply precast concrete in Singapore. This creates additional logistics process of having to transport the precast concrete from Malaysia to Singapore. The lower-skilled workers in Malaysia is also an indication that the utilisation of manpower during the production stage was not optimised. If such unnecessary processes are not removed, construction wastes in the form of defects and rework, overproduction, waiting and idle time, non-utilised resources, transportation, inventory, motion and extra-processing will be seen (BCA 2017 g; Ohno 1988; Womack and Jones 2003). For example, defects and rework are commonly observed due to poor workmanship as well as incompatibility of the precast concrete design to facilitate downstream production, logistics and installation. Overproduction of precast concrete occurs in the factory as the subcontractors doing the works would typically come in for a certain period only. This is for cost effectiveness but results in inventory. Motion is seen as logistics planning was not done properly resulting in unnecessary movement of the precast components prior to hoisting. Depending on how the design is done, the greater the number of precast components, extra-processing will be observed throughout the downstream production, logistics and installation stages (BCA 2017f). As a result, construction productivity and the value of the construction output will reduce. Lean construction is a way of designing the process flow and working methodology to minimise wastes to provide better value for the client (Ballard and Howell 2003; Cagliano et al. 2006). Lean construction has been used to optimise construction operations but failed to succeed in a big way (Arbulu et al. 2003; Bertelsen 2004; Hook and Stehn 2008; Nadim and Goulding 2010). Hence, there is need to address how leveraging on lean construction principles can help to streamline manpower and the precast construction process so that construction projects can be performed in an efficient and timely manner. In Singapore, the project productivity is calculated based on the total constructed floor area divided by the total number of site workers. Such monthly construction productivity data are to be submitted to BCA for projects with a Gross Floor Area (GFA) of 5,000 m2 or more (BCA 2019a). However, this monthly productivity data is not able to help contractors to assess the effectiveness of their controls put in place to optimise the total man-days utilised, both on-site and off-site. It is just a lagging indicator which measures the productivity outcome and not the activities, conditions

1.1 Background

3

or processes that are relevant to or may determine the productivity outcome. Even with enabling lean for precast construction, there is a need for contractors to have a means to know its effectiveness and decide what and how to act if the level of productivity is low. This will also motivate the team to act proactively and not trail behind by simply relying on the reactive and delayed nature of the project productivity data to know where they stand.

1.2 Research Problem and Question Many researchers and practitioners argued that the need for lean considerations in the precast construction industry is apparent. The study by Ray et al. (2006) have identified the application of lean manufacturing in the precast concrete industry to reduce wastes and improve their production operations. Lu and Yuan (2013) have investigated the waste reduction potential of precast construction by considering the upstream processes of manufacturing and transportation of precast components in the Hong Kong construction industry. Gao and Low (2015) have examined the application of the Toyota Way for construction projects in China to reduce costs while increasing productivity, reliability, and quality. The key wastes in the concreting supply chain in Singapore and its relationship with lean practise to enhance waste reduction performance have been studied by Low et al. (2016). Baijou and Chafi (2018) have examined the current state of lean construction implementation in the Moroccan construction industry and the benefits and barriers to adopt lean construction. Babalolo et al. (2019) have identified the different lean practices which were categorised into design and engineering; planning and control; construction and site management; and health and safety management for enhancing the productivity of the construction industry. According to Koskela (1992), contractors can remove unnecessary processes by applying the five lean steps in the deliverance of construction projects to bring about higher site productivity. Today, the industry leaders to follow for insights into lean construction are only seen in the US, United Kingdom (UK), Norway, Finland and Israel (Koskela 2017). Before the 2010s era, the Singapore’s construction industry does not seem to be interested in lean which could be due to the absence of lean construction standardisation such as guidelines (Mostafa et al. 2016). Besides the need to grow her pool of higher skilled workers, existing literatures recommended the adoption of technologies to cut manpower and improve construction productivity (Goodrum et al. 2010). In Singapore, precast construction is one of the key technologies promoted by the Building and Construction Authority (BCA) to enable the built environment sector to change the way buildings are constructed and to sustain productivity improvements in the long term. While contractors acknowledge the benefits of precast construction, the correlation between the degree of lean construction considerations in precast construction and productivity growth in terms of reducing the overall manpower requirements has yet to be studied in detail. Quantitative information proving the gains in total manpower reduction both on-site and

4

1 Introduction

off-site with the integration of lean construction and precast construction has also yet to be substantially proven, particularly in Singapore. With majority of construction projects adopting precast components, there is a need to mitigate the unnecessary processes to optimise construction productivity performance (Doran and Gianakis 2011). There is also limited evidence showcasing the existence of theoretical frameworks and process models assisting contractors to optimise for construction productivity management, triggered by considering lean in precast construction. Motivated by this gap in the current climate, this research addresses the following research question: How to enable lean in precast construction to reduce the total man-day requirements in Singapore?

If contractors continue with the traditional approach of construction by relying on low-skilled foreign workers, the benefits of adopting precast construction will not be fully realised and Singapore will end up with a far larger pool of foreign workers than she can possibly accommodate. Although precast construction has reduced workers on site, it has increased the number of personnel involved in the factory prefabrication. Hence, contractors are to continuously improve the precast construction process through minimising construction wastes and maximising value to improve productivity and reduce the overall manpower required for each project. There is also a lack of a unified theory to help contractors understand how to maximise productivity performance with the shift from on-site to off-site construction. Shared mental models theory have been identified to explain this phenomenon as lean studies have discussed factors that fit into the characteristics of shared mental models and should give insights as to the prevailing shared effects in the precast construction process. Babalola et al. (2019) discussed lean practices at the planning, design and construction stages as being influenced by factors such as teamwork and collaboration between all stakeholders such as clients, designers, contractors and suppliers in the process of executing different task in a project. Jamil and Fathi (2016) argued the need to improve a lean culture through being committed to open, frequent and genuine communication among all team members. Dave et al. (2016) examined the importance of accurate and timely information availability for the realisation of tasks. Bajjou and Chafi (2018) described lean construction techniques such as pareto analysis to identify the most important causes influencing the analysed task. They also elaborated on implementing a systematic approach to manage construction tasks while reducing waste and improving performance. Kim and Park (2006) identified training and team members’ attitude as key areas for successful lean construction implementation. By understanding the dynamics of teamwork and taskwork, contractors should act and position themselves in relation to these two paradigms (Ruona and Lynham 2004). Shared mental models integrate individual members’ biases such as beliefs, experiences and values and bring this collective knowledge or decision making to the specific situation to improve team learning and performance (Beratan 2007; Yang et al. 2008).

1.2 Research Problem and Question

5

Overall, the shared mental models is applied to systematically study the teamwork and taskwork of the precast construction process and to assess the nuances of each of the fourteen lean principles to bring about reduction of construction wastes and influence the total man-days to be utilised. These represent knowledge structures to support lean implementation for precast construction which correspond very well with the shared mental models theory. With that, the impact on the occurrence of construction wastes and the reduction in the man-day utilised grounded through shared mental models can be predicted to help contractors to understand the situations in which they find themselves, and gather all the findings in a conceptual model.

1.3 Research Aim and Objectives The aim of this research is to identify a set of leading indicators that classify precast construction projects in accordance with the manpower changes achieved through the construct of lean principles and shared mental models. This is to help the construction industry to predict the risk of low construction productivity and enable effective lean implementation to optimise the manpower effort required. Hence, the key deliverables and objectives of this study are: 1. To investigate the state of productivity in the local construction industry with focus on the manpower situation; 2. To review the precast construction methodology with understanding of the occurrence of construction wastes at each process; 3. To apply lean construction principles reinforced with shared mental models to make improvements to the respective process of precast construction which facilitates development of the leading indicator of precast productivity performance; 4. To develop a model to predict the leading indicator of precast productivity performance based on the extent of the occurrence of construction wastes with lean and shared mental models development; and 5. To validate the prediction model that can be used by contractors to classify the risk of low construction productivity performance at an early stage of the project. The purpose is to create a model that correctly maps the inputs to the output using historical data so that the model can be used to produce the output when the desired output is unknown. If the prediction model shows that there is a low risk of low construction productivity, it will be for the client or contractor to conduct a comprehensive cost-benefit analysis to implement further measures to maximise their productivity performance which falls outside the scope of the research. If the prediction model shows that there is high risk of low construction productivity, the analysis should tell the contractor if the extent of lean implementation is adequate as well as what aspects of lean they are lacking in which inhibits the reduction of man-effort. This will allow contractors to determine how to optimise the utilisation of the total man-days required when managing precast construction projects.

6

1 Introduction

1.4 Research Scope This research focuses on analysing the manpower requirements for lean construction implementation in precast construction projects in the Singapore’s construction industry. The research scope on precast construction can be justified as it is solely on structural works which accounts for at least 50% of the total Constructability Score (CS) and takes up a high proportion of construction time which is usually along the critical path. Given that precast construction can bring about a direct improvement in site productivityy, it is important to focus on this aspect to see how manpower savings can be derived not only on site but also off site. To influence the manpower requirements, this research acknowledged that the main contractor or precaster who manages the workers would be in a direct position to impact the lean construction considerations through shared mental models development throughout the precast construction process. Hence, the scope of this research is limited to team members from the main contractor’s site management team and precaster who is the subcontractor responsible for the precast concrete works as depicted in Fig. 1.1. Architectural and Mechanical and Electrical (M&E) coordinators are also included as there are interfacing works with the structural precast components in which their inputs must be sought early in order to prevent any construction wastes. For example, the location of sanitary wares and pipes must be planned upfront as it should not be located overhead of areas such as kitchen and server room. This is a mitigating approach in the event if there are any pipe leakages. Hence, the architectural coordinator should check for such issues and inform the architect to make the necessary amendments such as changes to the layout and this may impact the sizing of the precast components. In addition, M&E services may have to penetrate

Fig. 1.1 Team members from main contractor and precaster

1.4 Research Scope

7

through precast beams in order to allow for the required room height. The site structural engineer would then have to provision for the required beam opening for the M&E services and seek approval from the structural consultant. According to Laufer and Tucker (1987), planning was rated as the most important factor to result in construction productivity improvement and planning is the responsibility of the managerial level. Good planning before implementation is a critical requirement for successful delivery of any project as it is an opportunity to better understand the entire process (Gidado 2004). Supervisors and workers take instructions from the team members shown in Fig. 1.1 and hence are not included in this research as they have limited control over the implementation of lean construction principles which should be initiated and followed-through by the above-mentioned team members. By doing so, team members can lead the workers to produce beneficial future states that would not have occurred and prevent adverse future states that would otherwise have occurred.

1.5 Research Methodologies Figure 1.2 summarises the research design and methodologies regarding the research problem and objectives. Firstly, the state of Singapore’s construction industry in terms of productivity advancement will be discussed to provide an understanding of the issues, effectiveness of measures taken and outlook of the construction workforce in the years to come. Next, a comprehensive literature of precast construction and lean construction will be reviewed to set the boundary of this study by identifying the research gap. Based on the theoretical background, lean construction principles will be applied to make improvements to the precast construction process through minimising occurrence of construction wastes to maximise the utilisation of manpower. It is noted that high productivity arises with an effective team, where team members spontaneously help teammates fulfil their tasks, communicate openly, and give constructive feedback. This will also lead to stronger shared cognition about organisational performance which is made possible through the development of shared mental models (Scheutz et al. 2017). As such, the development of this conceptual model will use shared mental models as the backdrop to guide the process of gathering analysis of evidential data, indepth research in the international arena and engagement with industry practitioners. Choosing shared mental models as the explanatory, independent concept, and occurrence of construction wastes and total man-days required as the dependent concepts made it possible to build on insights from team cognition literature and formulate hypotheses about cross-level relatedness among these concepts. Such an analysis could clarify the distinction of the effects of shared mental models on enabling lean for precast construction. Using a set of questionnaires, data will be collected from precast construction projects in Singapore. The data will be analysed and validated through interviews to

Fig. 1.2 Research methodology

8 1 Introduction

1.5 Research Methodologies

9

identify the effects of lean construction considerations at each precast construction process on the manpower requirements. Next, the proposed model will be validated through a case study to justify its reliability and usefulness for contractors to extract actionable insights. Overall, the proposed prediction model serves as foundation to drive critical decisions, allowing better understanding and control of the various lean construction considerations to manage manpower requirements during the precast construction process.

1.6 Research Significance The significance of this study is aligned to the Construction Industry Transformation Map (CITM) which was launched on 24 October 2017. Despite the attention of DfMA in the second construction productivity roadmap rolled out in 2015, its adoption is only 20% as at 2017. Hence, the CITM aims to prepare the construction industry to capitalise on DfMA and to increase its adoption to 40% by 2020. Contractors are facing difficulties in managing precast construction projects as there are significant process change from on-site to off-site construction (Mao et al. 2015). Therefore, manpower savings have not been maximised, particularly off-site manpower. Local construction projects do not measure manpower savings through enabling lean for precast construction. There is an apparent lack of framework or methodology to understand the derivation of manpower changes by considering lean construction throughout the precast construction process. This study represents the first attempt to examine the key trends of precast construction adoption and identify the construction wastes and benefits when applying lean construction principles that affect the manpower deployment at each precast construction process. More importantly, the proposed model can help contractors ascertain their strong and weak areas in implementing lean at each precast construction process, ultimately reducing their manpower requirements.

1.7 Research Hypotheses The five research hypotheses formulated for this study are explained in Table 1.1 as follows.

1.8 Book Structure This book is divided into nine chapters.

10

1 Introduction

Table 1.1 Research hypotheses formulation and purpose S/N Hypothesis

Purpose

H1

The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction of construction wastes due to the development of shared mental models

As part of Objective 3, this is to find out the strength of dependency between the fourteen lean principles and ten shared mental models characteristics to reduce construction wastes in precast construction which are required to address the manpower situation as identified under Objective 1

H2

The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction in the total man-days used in precast construction

As part of Objective 3, this is to find out the strength of dependency between the fourteen lean principles to reduce construction wastes in precast construction and the eleven precast construction wastes that will result in manpower reduction addressed under Objective 2

H3

The reduction of construction wastes due to the development of shared mental models would have a positive effect on the reduction in the total man-days used in precast construction

As part of Objective 3, this is to find out the strength of dependency between the ten shared mental models characteristics to reduce construction wastes in precast construction identified in Chapter Five and the eleven precast construction wastes that will result in manpower reduction addressed under Objective 2

H4

The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the implementation of lean construction principles

As part of Objectives 4 and 5, this is to find out how the leading indicator of precast productivity performance would breach the specified threshold based on the extent of enabling lean in precast construction

H5

The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the development of shared mental models

As part of Objectives 4 and 5, this is to find out how the leading indicator of precast productivity performance would breach the specified threshold based on the commonality of precast construction team members’ shared mental models

Chapter 1 defines the research problem by first highlighting the background of the topic and establishing the research aim, research objectives, research scope, research methodologies as well as the research significance. Chapter 2 reviews the measurement of productivity for the construction industry, and highlights the key trends and aspects observed regarding Singapore’s construction workforce in shaping productivity improvement over the years. This is to bring attention to the research problem and reason the importance of this research. Chapter 3 analyses the relevant literature on precast construction from its foundation in DfMA, distinguish how precast construction affects the demand for manpower and reviews the precast construction process to identify the construction wastes. Inputs were also obtained from industry practitioners to aid in synthesising the

1.8 Book Structure

11

research problem and establishing the rationale behind the approach taken in this research to optimise the total on-site and off-site man-day requirements. Chapter 4 presents the literature review on relevant works in lean from its beginning, and its use to minimise construction wastes in the precast construction process. It highlights how the lean methodology can contribute to the reduction of the manpower effort in precast construction. It also underlines the research problem and rationalises the significance of this research on the need to eliminate unnecessary processes and streamline the total man-day utilisation. Chapter 5 introduces the conceptual model underpinned by the shared mental models theory, which sets the tone for the research deliverable to study the teamwork and taskwork of the precast construction process to enable the reduction of construction wastes and influence the total man-days to be utilised. Chapter 6 describes the research design and methodology adopted for this research. It presents how data was collected and analysed to create an optimal leanenabled approach for precast construction projects to maximise both on-site and off-site man-day savings. Chapter 7 examines the survey responses and the profile of the respondents, providing descriptive statistics which depict the overall trend in the results obtained. It also presents the data analysis, validated by the six interviews conducted, using inferential statistics such as the Spearman rank-order correlation coefficient. A neural network model was then developed to determine the predicted leading indicator of precast productivity performance. This is based on the percentage reduction in the occurrence of construction wastes with the implementation of lean construction principles and development of shared mental models among the precast construction team members. Chapter 8 validates and pilot tests the prediction model’s ability, through a case study, and investigate the relevance of the attributes to influence the occurrence of construction wastes and the total man-days used throughout the entire precast construction process as inputs to the model. Chapter 9 provides the conclusions and recommendations for further research and development.

Chapter 2

Construction Productivity in Singapore

2.1 Overview In Singapore, the government has introduced numerous initiatives to boost productivity in the construction industry. From the 1960s–1970s, the focus was labour-driven as part of Singapore’s industrialisation efforts. Productivity initiatives then took on new importance towards investment-driven to enhance the concerted efforts between labour and capital during the 1980s–1990s. Since 1996, the emphasis moved towards innovation-driven to develop its skills, technology base and capabilities. However, the results of fostering a productivity culture within the construction firms do not seem desirable despite strong support from the government. The current measures are no longer enough to help contractors achieve higher site productivity. Hence, this chapter provides an overview of the past and present state of construction productivity in Singapore to explain the manpower situation even with technology adoption. This chapter suggests that the construction sector in Singapore is still very reliant on foreign workers, whether off-site or on-site despite the industry embracing precast construction.

2.2 Productivity Measurement and Trend There is a whole array of ways to measure productivity within the construction sector. One method is called Total Factor Productivity (TFP) which is normally used by economists to measure how well weighted values of the rates of human, capital resources and other intermediate inputs are combined to produce more output per unit input (Jorgenson et al. 1987). However, TFP is hardly used in the construction industry as Singapore as well as the world’s major statistical agencies do not

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_2

13

14

2 Construction Productivity in Singapore

have a complete set of data to analyse TFP accurately. While TFP is a comprehensive industry-level productivity measure, its use within construction is limited and inefficient given the complexity of TFP measurement involving many factor inputs. Formerly, economic productivity refers to the value-added ($), that is the wealth created by a firm or industry, per worker and was the only yardstick to monitor construction productivity until 1991. The inaugural National Productivity Movement took place in 1981 to propel Singapore’s economy from the labour-driven to investment-driven phase of development. Since 1982 till 1993, the construction value-added per worker recorded an average of 3% growth per annum. This is lower than the average of 5.0% for the manufacturing sector and 4.5% for the whole economy during the same period and hence, concerns were raised on the poor construction productivity as compared to other sectors. Therefore, a taskforce was formed by the Construction Industry Development Board, the predecessor of the BCA, to work on this problem in 1991. The taskforce proposed measures to reduce manpower usage on site at a reasonable cost while maintaining design variety and workmanship quality. However, the construction value-added per worker started to dip by 13.7% in 1995 as shown in Fig. 2.1. Because of that, innovation was announced to be the pushing force in 1996 as productivity growth has reached its limit to be driven by quantitative increase in human and capital resources. However, value-added productivity was still registering a negative growth over the next few years which alerted the Ministry of Manpower and Ministry of National Development to step in and help the BCA. The Construction 21 (C21) exercise was initiated and a thorough investigation in 1999 concluded the need to restructure the processes, procedures, and practices, build up a knowledge and skilful workforce, as well as embrace technology. Overall, the annual

9.6% 8.1% 7.0% 4.0% 2.6%

2.4%

2.3%

2.7% 2.2%

0.5% 0.0% 0.0%

0.0%

1.9% 1.1% -0.5%

-2.4% -4.1% -4.3% -5.0% -5.3% -6.3%

-5.5%

Fig. 2.1 Annual percentage change in value added per worker. (Source BCA 2017b)

2.2 Productivity Measurement and Trend

15

percentage change in value added per worker have been fluctuating and the financial crisis have been acknowledged to be one of the reasons for the significant drop in the economic productivity. With effect from 2015, the Ministry of Trade and Industry (MTI) has used a new way of measuring economic productivity based on the real value-added per actual hour worked to account for the true amount of time spent on work. The construction industry is the most inefficient in Singapore, with an average of 0.75% growth per annum in the real value-added per actual hour worked from 2011 to 2016. The construction sector’s growth is only half of the overall growth in Singapore and the manufacturing sector is doing well with an average of 3.22% growth per annum over the same period (MTI 2019). According to Changali et al. (2015), construction productivity has been flat whereas productivity in manufacturing has nearly doubled in Belgium, France, Germany, Italy, Spain, UK, and US from 1995 to 2011 in terms of the real value-added per worker. Regardless, construction practitioners have highlighted that the economic productivity metric is inadequate as a sole measure of the sector’s productivity as it is strongly influenced by profit margins, market competitiveness and economic and sectoral business cycles. For example, value-added will be reduced if construction costs increase. In view of that, value-added productivity cannot robustly measure productivity growth and cannot be used to capture the impact of the construction industry over long periods. Consensus in recent studies have supported the use of physical productivity to measure the level of productivity achieved in the construction industry (Durdyev and Ismail 2016). Physical productivity refers to site productivity, which takes the total constructed floor area and divides it by manpower used on-site, measured in man-days. In Singapore, this was introduced in 1991 when the Construction Productivity Taskforce proposed an alternative productivity measurement due to the limitations associated with the value-added productivity method. This technique does not consider the professionals engaged in planning, financing, and design, as well as materials and components, plants and machineries used on-site. Effectively, physical productivity measures the process of constructing the building on-site. To emphasise, off-site production outputs which form part of the eventual building components are categorised under the manufacturing sector, not construction. The pull between physical productivity and economic productivity is evident as seen in the contradicting data in Table 2.1. From 2011 to 2018, the growth rate of economic productivity has been fluctuating but the growth rate of physical productivity is increasing for the first three years but remained stagnant for the next three years. This is because it cannot be generalised that the more profitable the construction industry or company, the more productive it can be. Besides the value-added component, it is important to measure what is happening on site. Improvement in site productivity means that fewer workers were used, indicating that construction was executed efficiently through good planning, adoption of technologies and deployment of a quality workforce. Hence, site productivity is more realistic in interpreting productivity for building projects as it will not be affected by changes in financial position.

16

2 Construction Productivity in Singapore

Table 2.1 Annual change in economic and physical productivity in the construction industry Percentage change over corresponding period of previous year (%)

2011

2012

2013

2014

2015

2016

2017

2018

Real value-added per actual hour worked at 2010 prices—economic productivity

3.2

1.7

−6.4

3.4

6.5

−1.6

−1.3

2.0

Site productivity—physical productivity

0.8

1.3

1.5

2.0

2.0

1.9

2.1

2.3

(Source BCA 2019a; MTI 2019)

The slow site productivity growth results triggered the launch of the first and second construction productivity roadmap in 2010 and 2015 respectively. Numerous solutions of similar prescriptions related to manpower, capital deepening and innovative capabilities were recommended to build on existing construction productivity initiatives to quicken the pace of bringing productivity to a higher level (Oglesby et al. 1989). Yet, the data suggests that actual growth is weak at best and the expected growth has not materialised as shown in Fig. 2.2 and Table 2.2. Ofori (2013) evaluated the effectiveness of C21 and found that much more can be done to improve construction performance. As meeting and satisfying regulatory requirements was the objective, efforts was not placed on providing an improved construction output (Dulaimi et al. 2004). Therefore, site productivity results remained low.

35% 30%

30% 27%

25%

24% 21%

20% 18% 15% 10% 5% 0%

20% 18%

16% 14% 14.07% 12% 11.74% 12% 10% 9.59% 9% 8% 7.64% 6% 6% 5.66% 4% 3.63% 3% 2% 2.09% 0.79% 15%

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Fig. 2.2 Cumulative site productivity growth. (Source BCA 2019a)

Actual Target (lower bound) Target (upper bound)

2.3 Manpower Requirements Table 2.2 Overall site productivity

17 Year

m2 per man-day Actual site productivity

Lower bound target

Upper bound target

2011

0.384

0.389

0.392

2012

0.389

0.396

0.404

2013

0.395

0.404

0.416

2014

0.403

0.412

0.429

2015

0.411

0.421

0.442

2016

0.419

0.429

0.455

2017

0.428

0.438

0.469

2018

0.438

0.447

0.483

(Source BCA 2019a)

2.3 Manpower Requirements Manpower, being a significant resource in construction projects, is required to plan for productivity implementation. Hence, it is important that the mind-set, work attitudes and expertise of the workforce are aligned to the goals of enhancing site productivity growth (El-Gohary and Aziz 2013; Rojas and Aramvareekul 2003; Soekiman et al. 2011). As a small country with people as her only resource, this has been Singapore’s focus for a very long time. Researchers and policy makers believed that productivity improvements can be achieved by educating and training people. Construction firms need to invest in effective human resource practices that support continuous growth and motivate the workforce to drive employees’ involvement, commitment, teamwork, improvements, and innovation at all levels. According to Alagaraja (2014), the leaders of the construction firms are responsible for influencing and inculcating such a culture to drive productivity growth. Since 1992, the Singapore government relaxed its rules to allow local contractors to bring in foreign workers as a temporary solution to ease the labour shortage (Tan 2000). Although these workers must attend and pass basic courses conducted by overseas training centres certified by BCA prior to coming to Singapore, they remain largely unskilled. Anecdotal evidence suggests that these migrant construction workers typically come from Bangladesh, China, India, Malaysia, Philippines, Sri Lanka, and Thailand (Ling et al. 2012). This workforce has been identified as the source of the industry’s poor productivity, quality, and safety record (Low et al. 1999; Abdul-Rahman et al. 2012). Over the years, the foreign-worker levy and dependency ceiling which controls the proportion of foreign to local workers have had to be revised upwards many times to reduce Singapore’s reliance on low-cost, low-skilled foreign workers. The management of foreign workers also involves a series of work passes with different benefits and obligations depending on the worker’s qualifications and skills. Despite these restrictions, it is evident that the construction sector

18

2 Construction Productivity in Singapore 600 500

Thousands

400 300 200 100 0 Total No. of Workers

2010 2011 2012 2013 2014 2015 2016 2017 2018 380,700 402,700 441,800 477,100 491,400 500,000 489,200 450,900 443,800

No. of Foreign Workers 272,900 292,500 327,400 359,300 369,000 375,800 365,700 333,000 327,600 No. of Resident Workers 107,800 110,200 114,400 117,800 122,400 124,200 123,500 117,900 116,200

Fig. 2.3 Employed foreign and resident workers in the construction industry. (Source MOM 2019; MTI 2019)

in Singapore is still very reliant on migrant or foreign workers as shown in Fig. 2.3. Foreign workers account for an average of 74.05% of the construction workforce between 2010 and 2018. This means that bulk of the manpower requirements in the construction sector was filled up by foreign workers. Instead of having inexperienced transient foreign workers waiting for instructions, employing higher skilled workers who can work with minimal supervision will help to raise construction productivity. A higher skilled workforce will be able to generate 20–30% more construction output, but they are currently concentrated in larger construction firms. However, the higher-skilled and experienced workers are unevenly distributed across the construction firms in Singapore. Inevitably, a proportion of construction firms continued to rely on foreign workers who are largely lowskilled so that they can fulfil their obligations amid the strong demand for construction in Singapore. A strong core of professionals, managers, executives, and technicians (PMETs) is also required to drive productivity initiatives so that construction productivity can make a significant progress. However, local construction-trained PMETs are not attracted to the construction sector in Singapore which is causing a labour shortage. This situation, known as manpower leakage, is also observed in the construction industry in both developed and developing countries (Ling et al. 2012; Yi and Chan 2013). Additionally, the transient construction workforce presents a challenge for the workmanship quality and the pace of productivity growth in the construction projects. In 2015, the Singapore Contractors Association Ltd (SCAL) introduced an online

2.3 Manpower Requirements

19

job portal known as Foreign Construction Worker Directory System (FCWDS) to match construction workers on expiring work permits with other suitable construction firms. SCAL hopes to reduce the number of foreign workers leaving Singapore if their employers do not renew their work permits when they do not require the manpower. This could be due to the low volume of jobs of that employer which prompt them to let the foreign workers go. At the end of the day, investments that have been put into these individuals will be lost. With the FCWDS, foreign construction workers can list their skill sets, certification, and years of construction experience in this database, thus allowing construction firms to better source for trained workers. These construction workers would also be able to secure new jobs swiftly without a lapse in earnings because of the processing time or having to pay high recruitment fees to agents. Through hiring existing workers instead of new workers, more skilled and experienced workers are retained and the quality of the construction workforce in Singapore will likely improve. Helping employers to tap on the existing pool of construction foreign workers through the FCWDS is a drastic change from the normal way of how recruitment is done in the construction industry. It brings productivity gains with the reduction in recruitment time and better matching of workers to meet projects’ needs. Construction firms will be able to save on the costs required to replace these workers, who are safety-trained and understand local requirements and regulations. Moreover, the learning curve for these workers is minimal. In 2016, only about 2% of the foreign construction workers in Singapore are utilising this platform. There is still room to grow the number of successful matches and get more players, particularly smaller contractors on board. Even though this is a new recruitment approach, the slowdown in the construction market could be another reason for the low figures.

2.4 Technology Adoption Technological advancements can bring about many benefits, of which, the ability to improve productivity is widely known (Goodrum et al. 2010). There have been significant technical improvements in construction techniques, machineries and methods which changed many construction processes as well as the workmanship quality, resulting in productivity gains (Goodrum et al. 2009). Contractors need to break away from the traditional culture of adopting safe design and construction technologies. They should aim to achieve beyond the norm and find alternative ways to enhance the workflow and construction environment to raise construction site productivity. Yet, it is questionable if contractors are ready to embrace this change. Contractors must ensure that there are some profits and if the benefits of adopting productive technologies does not outweigh the disadvantages, they will not be concerned about improving site productivity. In 2011, a new component called CS was introduced under the enhanced buildability framework for the construction of buildings with GFA of 5,000 m2 or more. The aim is to encourage builders to move away from traditionally labour-intensive

20

2 Construction Productivity in Singapore

construction methods and switch to more labour-efficient construction processes and labour-saving technologies (BCA 2017d). However, the level of technology adoption remains unevenly distributed across the construction firms in Singapore. Despite the availability of funding provided by the government, a significant proportion of construction firms are reluctant to implement new technologies to achieve a higher CS. Moreover, in 2016, BCA identified 35 technologies under seven clusters to enable the built environment sector to change the way buildings are constructed and to sustain productivity improvements in the long term. However, technology adoption will still have to be implemented by the foreign workers and the manpower requirements are only shifted off-site instead of on-site with slight manpower savings (Salem et al. 2005; Yi and Chan 2013). Precast construction technology is the way forward in the construction industry to boost site productivity. Hence, there is a need to achieve more aggressive manpower savings so that more contractors will be drawn to implement precast construction even if the project is not subjected to regulatory conditions.

2.5 Gaps in Current Research In summary, strides have been made to reduce the reliance on foreign workers but there are still deep-seated problems holding back its progress which inhibited the growth of site productivity. Even though precast construction has been around since the 1960s, manpower utilisation needs to be further improved as can be seen from the slow site productivity growth and numerous efforts being introduced over the years as explained in this chapter. There is a need to strengthen the contractor’s fundamentals so that the construction industry can deliver high quality and productive work with lesser manpower off-site and on-site. This will also help to raise the adoption of precast construction so that it is not solely driven by the regulatory requirements as per the current context.

Chapter 3

Precast Construction

3.1 Overview The industry needs to change its design approach and construction processes, with an emphasis on moving towards precast construction to improve buildability upstream and ensure constructability downstream so that lesser foreign workers or manpower is required. With less site work, precast construction provides a safer construction environment as workers do not need to work-at-height for prolonged period and only need to handle simple tools for screws, bolts, and nuts. The workmanship quality can also be controlled, and construction processes can be streamlined through greater automation in factories. Furthermore, the use of precast construction can lower the level of dust and noise for neighbourhoods in the area during construction on site. However, contractors are facing much problems to build up their capabilities to implement precast construction in a manner that will minimise construction wastes such that lesser total man-days are required. Hence, this chapter reviews the precast construction methodology based on the DfMA concept, distinguishing how precast construction affects the demand for manpower. This chapter also covers the whole end-to-end process of precast construction to identify the construction wastes which are commonly observed at each process. The literature review in this chapter and consultations with industry practitioners suggest the importance of minimising construction wastes throughout the precast construction process so that the industry can reduce the total number of man-days and reliance on foreign workers. The fourteen consultation sessions were conducted through face-to-face interviews, emails and phone calls and details of the practitioners are shown in Appendix A.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_3

21

22

3 Precast Construction

3.2 Design for Manufacturing and Assembly DfMA is an approach to design that focuses on ease of manufacture and efficiency of assembly. It can be broken down into the Design for Manufacture (DFM) and Design for Assembly (DFA) concepts which emerged in the automotive sector in late 1960s (Bogue 2012). DFM and DFA were pursued due to the need to produce large numbers of consistently high-quality products very efficiently and cost effectively. DFM is about making individual parts that are easy to produce whereas DFA addresses the means of assembling them. This is done by simplifying the product design to minimise the number of individual parts and ensure that the remaining parts are easily assembled. Each part will have its specified tolerance that should not affect the resultant product quality when assembled. With fewer parts to be manufactured and assembled, there will be few interfaces between parts and fewer parts will fail (Panwar et al. 2015). Due to the reduced complexity, the application of DfMA will lead to reduced labour, better quality and improved productivity. In the construction sector, the term “prefabrication” has been more commonly used which is essentially DfMA (Gibb and Isack 2003; Goulding et al. 2015; Lawson et al. 2014). In Singapore, the greatest extent of prefabrication can be seen in public residential buildings as the Housing and Development Board (HDB) maximises the precast components used to about 70% by volume of the entire structural concrete used during the construction stage for every project (HDB 2017). Utilising the concept of DfMA, HDB have been standardising its floor plan design and designing facades of adjacent pairs of rooms as one building component. With the help of a greater potential for automation and more intelligent management systems under controlled factory conditions, prefabrication offers aesthetic solutions with various shapes and curves, precise dimensional accuracy, and consistency in finishes and textures (Chen et al. 2010). Spearheading the prefabrication technology by leveraging on the Automated Precast Production System (APPS) technology, HDB has developed the Large Panel Slab (LPS) to produce custom-made room size precast floor panels. APPS is highly efficient as there is a conveyor belt system to transport precast moulds from each operation-specific station to the next which means that the production capacity of the plant can be significantly increased compared to conventional precast plants. Other examples include precast sandwich wall, precast flat slab, precast connector, prefabricated mesh and cage, curtain wall, hollow core slab, drywall and lightweight precast concrete panel. The adoption of these systems can reduce the demand for manual labour, material wastage and allow for more complex designs to be fabricated and installed quickly (Kazaz and Acikara 2015). In fact, there used to be this notion that precast construction are mobile or temporary structures that are inferior in quality to traditionally constructed buildings (Gunawardena et al. 2014). However, designers and contractors now find that prefabricated components can not only shorten the construction schedule but also boost quality as evident from the revival of precast construction implementation worldwide in the past decade (Sinclair et al. 2012). Clients are demanding more

3.2 Design for Manufacturing and Assembly

23

efficiency from contractors so that they can start generating revenue with an operational building which forced contractors to build up their skills and knowledge in precast construction. To underpin the importance and raise awareness of this dormant concept, Australia launched the world’s first Modular Code of Construction Handbook for industry best practice in 2017.

3.3 Classification In Singapore, the Code of Practice on Buildability has ranked various DfMA technologies into four levels accordingly to the degree its usage will help to improve site productivity. BCA has further classified them into three categories – Structural, Architectural as well as Mechanical, Electrical and Plumbing (MEP), as shown in Table 3.1. The higher the extent of prefabrication such that lesser work is required on site, the higher the class of DfMA which means higher site productivity (Kazaz et al. 2016).

3.3.1 Prefabricated Prefinished Volumetric Construction PPVC is the only fully integrated system classified under first class in the Code of Practice on Buildability. PPVC involves the assembly of multiple modules complete with architectural and MEP components that are produced off-site and installed on site in a Lego-like manner. The PPVC carcasses can be concrete, steel or a hybrid of both and the choice mainly depends on cost, the required performance and perception of owners. As compared to concrete, steel has a higher strength to weight ratio which makes it lightweight (about 50% lighter) and yet strong. One major difference is that the partition walls in Steel PPVC can be designed to be removed to offer the clients a more flexible usage planning and arrangement of the floor. However, steel has a relatively poor fire resistance in comparison to concrete and its strength can be compromised significantly when exposed to extreme temperatures (Rackauskaite et al. 2017). Though designers can reduce the foundation loads for steel PPVC structures, there is added consideration to meet fire protection requirements. Recognising the importance of quality assurance and control in the production, the PPVC Manufacturer Accreditation Scheme was launched on 29 March 2016. The accreditation sets the process for PPVC manufacturers to produce high quality PPVC systems and maintain the good quality standards through system audit and in-process assessments. Table 3.2 summarises the PPVC scope of work though there could be slight variations depending on the design of each project and the choice of system. Upon completion of the PPVC carcass, architectural and MEP works shall continue. Generally, structural slab, beam, and walls with MEP cast-in items and wall or slab penetrations are assembled as module in a factory in Malaysia. Wall

24

3 Precast Construction

Table 3.1 Classification of DfMA by disciplines Class

Structural

First (fully integrated system)

• Prefabricated Prefinished Volumetric Construction (PPVC)

Second Upper (fully integrated sub-assemblies)

• Mass Engineered • Prefinished wall with MEP services Timber • Prefinished ceiling with MEP services • Prefabricated Prefabricated MEP modules integrated with Volumetric work platform/catwalk Construction • Prefabricated Bathroom Units (PBU) • Structural steel with innovative connections • Steel-MEP floor system

Second Lower • Structural steel (advanced • Unitised curtain prefabricated systems) wall • Prefinished slab

Third (prefabricated components)

Architectural

• Prefinished wall • Prefinished ceiling

• Integrated precast • Prefabricated ceiling components with onsite dry comprising at least applied finishes two elements (e.g. multi-tier column/wall, double bay façade wall) • Mechanical connection for precast column/precast wall (horizontal joints) • Mechanical connection for precast wall (vertical joints) • Precast external wall with cast-in windows • Prefabricated wall/façade with onsite dry applied finishes • Prefabricated slab with onsite dry applied finishes

(Source BCA 2017e)

MEP

• Prefabricated MEP modules (e.g. pipes, cable trays/trunking, etc.) • Prefabricated MEP plant module (e.g. pump, compressor, etc.) • Prefabricated and pre-insulated duct for air-conditioning system • Flexible sprinkler dropper • Flexible water pipes • Common mechanical and electrical bracket (at least three services)

3.3 Classification

25

Table 3.2 General scope of work for PPVC Design stage

1. Structural design 2. MEP design 3. Architectural design 4. Compliance with statutory requirements

Production stage

Logistics stage Installation stage

Factory (Local/Overseas)

Fit-Out-Yard (Local)

Construction site (Local)

1. Mould production 2. Sub-assembly and framing 3. Mechanical and electrical cast-in items 4. Other cast-in items and pipeworks 5. Structural ponding test 6. Autoclaved Lightweight Concrete (ALC) panels installation 7. Waterproofing 8. Water ponding test 9. Mechanical and electrical for ALC locations

1. Temporary metal deck 2. Dry walls 3. Floor screed 4. Windows frames 5. Tiling 6. Carpentry works 7. Sanitary fittings 8. Curtain wall 9. MEP fittings 10. Ceiling works 11. Painting (base coat) 12. Balcony railings 13. Airconditioning ledge railings 14. Glazing works 15. Door frames/panels 16. Inspection and tests

1. Protection for finishing 2. Load and transport to site 3. Unload and touch-up on site 4. Lifting and hoisting

1. Continuity bar installation 2. Slim box connection 3. Mechanical plate installation 4. Stopper for grout 5. Vertical or horizontal grout 6. Slab to slab connection 7. Balance wet trade works at unit corridor 8. Balance touch up works for walls between lower and upper module 9. MEP connections for module to module 10. Balance ceiling works 11. Balance painting works 12. External sealant

panels are then propped with temporary bracing prior to transportation to the fit-outyard in Singapore. In the fit-out-yard, window frames and door frames are installed. Waterproofing and tiles are laid, avoiding areas with temporary propping and there will be four lifting points at the edge of each module. The modules are then transported to site. Alternatively, some PPVC manufacturers ship the 2D panels to the

26

3 Precast Construction

Table 3.3 Minimum level of finishing and fittings to be completed off-site Element

Minimum Level of Completion Off-Site

Floor finishes

80%

Wall finishes

100%

Painting

100% base coat, only final coat is allowed on-site

Window frame and Glazing

100%

Doors

100%, only door leaves allowed for on-site installation

Wardrobe

100%, only doors are allowed for on-site installation

Cabinet

100%, only doors are allowed for on-site installation

M&E including water and sanitary pipes, electrical conduits and ducting

100%, only equipment is allowed for on-site installation

Electrical sockets and light switches

100%, only light fittings are allowed for on-site installation

(Source BCA 2017e)

factory or fit-out-yard in the destination country for assembly as it could be more cost effective. The Code of Practice on Buildability has specified some margins for buildings which are mandated to use PPVC, allowing certain level of finishing and fittings to be completed on-site as shown in Table 3.3. Upon removal of the temporary props after lifting and installation including the temporary metal deck which is used to protect the module, the joint areas are to be filled up and tiled over. Finally, window glazing is installed and module to module interface detailing are performed.

3.3.2 Prefabricated Volumetric Construction Instead of PPVC, some contractors have adopted Prefabricated Volumetric Construction (PVC) which is classified under the second upper class in the Code of Practice on Buildability. This happens when production of the modules is done at a neighbouring country and not at the place of the construction site. Some contractors only do PVC as they find it challenging to deliver the fully fitted and furnished modules on site as the fittings and furnishings are susceptible to damages such as cracking tiles during the transportation process as well as due to exposure to the inclement weather conditions and uneven movement of modules during handling (Hwang et al. 2018). It is also difficult to manage the quality control aspect during the fitting out as these works require higher skilled workers and close supervision and such manpower are more readily available locally. Otherwise, contractors will have to incur higher

3.3 Classification

27

upfront cost of training new workers and post competent people over to oversee the works. As the sources of approved materials are generally in Singapore, the contractor would have to export the materials overseas and subsequently deliver the PPVC modules back. Unless the materials sourced from the country of the factory are approved, there will be a need to deal with tax issues which means more effort is required. Some contractors have set-up fit-out-yards in Singapore to deal with these hurdles when their factories are located overseas while those who are more skilled can complete the fitting out works in their overseas factories.

3.3.3 In-Built Bathroom PBU, which is classified under the second upper class in the Code of Practice on Buildability, can be in-built as part of the PPVC module. It is mandatory to use for non-landed residential Government Land Sales sites since 1st November 2014. PPVC is a larger version of PBU and there is now a rise of in-built bathroom within the PPVC module. Generally, each PBU will be self-contained with removable ceiling panel, precast concrete slab, galvanised steel cassette wall panel, sanitary ware fixtures and fittings, full concealed electrical, water and sanitary piping and wiring which are done in the factory.

3.3.4 Advanced Prefabricated Systems and Prefabricated Components Advanced precast is classified under the second lower class in the Code of Practice on Buildability as while precast members are being connected, propping is not required. This is because advanced precast makes use of mechanical connectors such as column shoes, beam shoes and/or brackets to connect the precast members together. Traditionally, the prefabricated components are jointed in a cast in-situ manner which involves wet works and more manpower effort. Propping or falseworks are required to temporarily hold the members while the connection is being done and time is also required for the concrete to gain strength. With advanced prefabricated system, it is more productive as lesser man-day is required to do the works. Larger precast panel can also be used due to the stronger bolted connection which means lesser joints and lesser man-day required to do the connections on site. Advanced prefabricated systems are also about integrating precast components with other elements off-site. For example, prefabricated modules with pipes, cable trays and trunking can be integrated into a sub-assembly off-site

28

3 Precast Construction

in a factory-controlled environment. This improves the quality of works and enable fast and easy installation on-site.

3.4 Stakeholders Having operated the traditional way for decades, many contractors are unwilling to experiment with new ways of working with DfMA technologies (Gao et al. 2018). It is important that there is management oversight of the precaster by the main contractor to ensure that the construction method is adhered to. Despite shifting the scope of subcontractors to the factory with DfMA, there will be some difficulties in terms of integrating with other construction operations as they are unaware of the operational sequence of the entire project due to the lack of a common information platform among the subcontractors (Ofori and Lim 2009). In the traditional approach, subcontractors usually come in much later which hinders upfront collaboration among the different stakeholders. The interaction among the various stakeholders is fragmented and lacks depth, and is yet to reach the scale needed to deliver DfMA projects. This is not just between the precaster and main contractor. It is also important to get subcontractors involved as early as possible so that they can share their inputs, reducing the need to make changes (Yin et al. 2014). Otherwise, there will be reworks which means more effort is required, resulting in longer construction time, higher costs, and reduced workmanship quality (Locatelli et al. 2013; Maturana et al. 2007). Architectural and engineering consultants must also know about DfMA so that the prefabricated components can be configured to be buildable and reduce dependence on labour. If DfMA is going to become the norm, consultants will have to work harder creating more interest on the facades and making mass customisation achievable even with prefabricated components of different shapes and rooms having different layouts. Hence, it is critical that all stakeholders thoroughly consider and take efforts to eliminate the commonly encountered issues upfront during the design stage to facilitate downstream processes.

3.5 Considerations During the Process of Precast Construction The following shall describe the construction wastes observed and the causes in the process of precast construction which plays a pivotal role in influencing the considerations to be made to streamline the manpower effort.

3.5 Considerations During the Process of Precast Construction

29

3.5.1 Design 3.5.1.1

Early Contractor Involvement

In many countries such as the US, UK, Australia, and Singapore, the two most used procurement methods are the traditional design-bid-build (DBB) and the design-andbuild (DB) systems (Ling and Kerh, 2004). In Singapore, only an average of 11.46% of building projects were based on DB between 2004 and 2013 (BCA, 2017a). This means that parameters of the project are largely defined by employers who then invite construction firms to tender for contracts based on DBB. From the perspective of enabling inputs from precasters and contractors, DB projects or projects with an element of early contractor involvement (ECI) such as design-develop-build is a better mode of procurement than DBB. The procurement strategy comparison of DBB and DB with ECI is shown in Fig. 3.1. Hence, the DB approach is commonly seen in Korea and Japan where one construction firm have both design and construction team to seamlessly manage the project. ECI encourages both design and construction professionals to work towards the client’s interests and jointly collaborate to achieve integrated design and construction (Tam et al. 2007). The client will be able to harness the latest knowledge and technologies from the contractors as they have the expertise to provide alternative solutions that are more efficient and may provide better value for money as well. The architect will then be able to design a facility that can be built within the client’s budget as opposed to only discovering budget issues after all the drawings have been completed. In DBB, design changes may be required to suit the prefabrication process, and this means extra manpower effort is required. With the architect and contractor working together, there will be less chance for change orders because of constructability issues, driving manpower usage to the minimum (Minami

Fig. 3.1 Comparison between DBB and DB with ECI

30

3 Precast Construction

et al. 2010). Alternatively, the design can be open enough to allow for adjustment of the construction details while ensuring a buildable design that can still improve construction productivity.

3.5.1.2

Standardisation, Simplification and Single Integrated Elements

The constraints on the 3S principles of Standardisation, Simplification and Single Integrated Element relate primarily to dimensional attributes and include issues relating to height, span, transport, weight and space which will directly impact the manpower required. A fundamental characteristic is the need to overlay plans onto predetermined templates to arrive at the most optimal solution (Doran and Giannakis 2011). The consultants will have to work closely with the precaster and main contractor to apply the 3S principles for the all the prefabricated components. The placement of MEP components, corridors and wet areas will also affect the modularisation and hence, it is important to take these design considerations into account upfront. The prefabricated components should be standardised and simplified as far as possible to maximise the use of each mould during production and minimise the number of components so that lesser work will be required during on-site connections and handling can be better managed (Hwang et al. 2018). This will also reduce the manpower required during transportation, lifting and installation downstream. The maximum width and height of each prefabricated components must take into consideration so that they can be transported to site based on the traffic regulatory requirements.

3.5.1.3

Interfacing Coordination and Connection

Interfacing coordination relates to decisions concerning how the precast members fit together, connect and communicate. With more interfaces and more complex interface, the chances of construction wastes occurring will be increased (Panwar et al. 2015). More man-hour is required for interface management both on-site and off-site when the design incorporates wide spans and greater heights. If the connections are not properly done at one area, subsequent connections will not be accurate. There may be defects and extra-processing to rectify the situation. In the event when the design consists of precast systems and traditional cast insitu construction, the integration strategy should be well-planned as there is a lot of compliances with BCA stringent structural interface requirements to allow for lateral stability. This will happen at the connections to lift shaft, household shelter and staircase shelter which are easier to be constructed in the traditional cast insitu manner. Hence, an integrated team approach is required to coordinate among the various disciplines and numerous suppliers and subcontractors to identify and address all the risks involved (Romano 2003). There should also be a disciplined method to manage the communication, synchronisation, and responsibility of the

3.5 Considerations During the Process of Precast Construction

31

communal boundaries among the various parties, phases and physical entities to yield significant optimisation of manpower (Bankvall et al. 2010).

3.5.1.4

Alignment and Construction Tolerance

The Construction Quality Assessment System (CONQUAS) measures the workmanship quality achieved in a completed building project in accordance with the contractual specifications. The consultants must be aware to build in high quality in the precast construction such as for the verticality, squareness, concrete cover, cross section dimensions, opening size for door and window, column position, bolting, tile lippage and floor and wall evenness. The construction tolerance of precast construction is more stringent than the CONQUAS requirements as non-conformances that breach the threshold will greatly affect the installation on site. Due to the strict alignment and construction tolerances, each module is bespoke and are rarely interchangeable between different levels even if it is in the same grid and typology (Staib et al. 2013). Hence, the various stakeholders must work closely to ensure that the correct module is being installed or there will be construction downtime to correct any misfits.

3.5.1.5

Accessibility for Assembly

On-site installation sequence should be catered for in the layout design upfront so that there is accessibility during assembly (BCA 2017f). This is especially for non-critical path installation to avoid clashes with other on-site trades. For example, in PPVC, there should be access from outside the module such as from the adjacent room for final installation and connection works to prevent damages within the module which causes reworks. MEP fittings and connections should be located near the edge of the module with sufficient headroom so that there is no obstruction during the final connections and workmanship inspection. Shallow floor trap should be used for the in-built bathroom to simplify on-site connection works as connection to the soil stack is only required from the side of the PBU. Otherwise, conventional floor traps will have to be connected from underside of the PBU which is more time-consuming. Furthermore, routing of M&E services can be done outside the module to reduce connection works within and lower the risk of damage to internal fittings and finishes which will otherwise lead to defects and reworks which increases manpower handling.

3.5.1.6

Design Approvals

In contrast to the traditional construction approach, design must as far as possible be finalised at an early stage for precast construction projects. This is so that the precaster can optimise the design of the prefabricated components, standardise and minimise

32

3 Precast Construction

the interfacing joints. Efforts are shifted forward into the design and planning of the job and key activities must be thought-through in advance so that high risk tasks can be adequately planned (Molloy et al. 2012). Architectural as well as MEP works should be planned upfront together with the structural works before production take place. There will be abortive works if this was not done property and changes are required. However, clients tend to take a long time to approve all submitted layouts, materials and colour scheme. If design is not freeze early on, factory production drawings cannot be generated. There is no room for error once the precast components are produced as the consequences in terms of time and cost will be substantial (Lee and Kim 2017). Any fine-tuning required on site will incur additional effort and often, flexibility for changes are very little.

3.5.2 Production 3.5.2.1

Factory Location and Capacity

A huge land space is required for producing the precast components. Hence, contractors in land scarce Singapore have located their factories in neighbouring countries like Malaysia and China. However, they are concerned that there would be insufficient demand and the huge facility set-up would be vacant or largely unoccupied which means there is a high risk of extra-processing. Thus, many of the precasters are teaming up with their overseas partners to set up the factory instead of holding the assets themselves to lower their risk. The precasters would have to secure sufficient projects to ensure that there is no downtime at the factory. If there is a need for a fit-out-yard in Singapore, the location to the construction site is critical. This is to minimise the man-hours required to transport the precast components from the factory to the fit-out-yard and subsequently to the construction site. There will be construction downtime in the event of bad weather conditions and heavy traffic, especially at the customs, causing the manpower deployed to be left idle. Inventory space at the fit-out-yard is typically more than at the factory to cater some buffer in the event there are some problems during the fabrication at the factory and transportation to the fit-out-yard. With that, the manpower deployed could still be utilised. Overall, the need to manage multiple sites in precast construction projects would require more management effort as compared to traditional cast in-situ projects.

3.5.2.2

Plant and Machinery Capabilities

The precaster should determine the number of production lines to set-up based on the requirement of the precast components that needs to be produced per day and given the size of the factory and fit-out-yard. However, there are difficulties in coordinating

3.5 Considerations During the Process of Precast Construction

33

fabrication and installation because the daily production rate for different components differ as was the fabrication and installation rates. The precast components are fabricated in a controlled environment which enhance precision and significantly lower material waste. However, some contractors may overlook on executing the works in a sheltered environment to protect the precast components from external elements. This will lead to defects and reworks incurring more man-effort.

3.5.2.3

Total Quality Management

There are added challenges to ensure the quality control of precast construction bearing in mind the stringent construction tolerance. In this regard, numerous inspections must be done at every stage of the production in the factory which substantially adds to the man-effort required as compared to cast in-situ construction. In the short run, the objectives of quality and lesser man-effort seem to be contradictory and reducing labour means sacrificing quality. This is because attempts to improve quality causes disruptions and delays that translates to reduced output if there are insufficient man-effort to rectify the situation. When viewed on a long-term basis, any improvement in quality should translate directly into reduced defects and less rework (Lee et al. 2007). Total Quality Management (TQM) is a management theory that can be integrated into the precast production process to result in continuous improvement with visions of better efficiency and competitiveness (Selladurai 2002). The construction industry should search actively and continually for ways to improve quality to reduce the manpower required. To ensure quality, the prefabricated components should be lined up according to how they will be installed to strengthen the alignment and prevent defects and reworks upon installation on-site which incurs more manpower effort. This is important because if one component is not installed correctly, the rest of the modules will not be aligned. As an example, the quality-circle approach can be harnessed to improve qualityrelated issues and solve problems of construction waste reduction as well as resource use. TQM involves people, places great emphasis on leadership engagement, addresses organisational risks and opportunities and have a focus on customer. Therefore, TQM practices could be used to optimise the man-effort to be utilised by ensuring interrelated processes function as a coherent system and managing stakeholder relationships.

3.5.2.4

Human Resource Management

The construction industry also needs to look at the skillset of labourers and the currency of what is being taught in educational institutions to ensure that people are trained to do precast construction. BCA is offering incentives and developmental programmes as shown in Fig. 3.2 to help construction firms to develop their workforce and employ new technologies to transform their construction processes so that

34

3 Precast Construction

Fig. 3.2 Construction Productivity and Capability Fund schemes. (Source BCA 2017c)

lesser manpower is required. This starts with ensuring that students entering the construction workforce are capable to manage the changes in the industry based on the newer forms of technologies as well as soft skills such as people management. Relevant skills across the various disciplines will be incorporated into the curriculum of institutes of higher learning so that students attain deeper industry knowledge. In addition, BCA works actively with contractors by helping them to draw up development plans to raise their construction engineering capability. There is also the Construction Registration of Tradesmen scheme which provides the workers a clear

3.5 Considerations During the Process of Precast Construction

35

career progression path and sets the context for training and skills upgrading for the construction workforce. As precast construction is a revived concept, there are limited courses available in the market and the labourers are taught in-house through trade demonstrations. Trade demonstrations are performed to ensure that workers are aware of the expectations and take note of the lessons learnt prior to actual works on site. If these are not completed satisfactorily, construction wastes are inevitable. The contractor will have to correct any deficiencies and inspections will have to be repeated, resulting in more manpower effort incurred. Once the workers become familiar and experienced, they will be able to minimise construction wastes and do their work fast and efficiently with good workmanship. From the shared mental model perspective, this is an important adaptability phase to also allow team members to adjust their strategies in response to new tasks demanded of the workers (Dhanaraj and Khanna 2011). Therefore, the development of shared mental models is critical in the process of nurturing an encouraging atmosphere to move from the traditional construction approach to precast construction. This was challenging to some contractors and labourers as precast construction is neither wholly construction nor wholly manufacturing but rather a hybrid of the two and as such does not fit neatly into common trade classifications. There may be some resistant to change and reduced level of productivity at the initial stage due to an incomplete or inaccurate understanding of their role in the precast construction structure. Therefore, it is important to supervise the workers at the factory and fitout-yard on top of on-site supervision which means more effort is required to ensure a successful shift. The adoption of precast construction does not change the profile of skillset required of labourers. Similar to the traditional construction approach, only architectural trades such as waterproofing for internal wet areas, ceramic tiling, marble and granite finishes, timber flooring and aluminium window would require higher skilled workers. Overall, having manpower of the appropriate skillset should reduce the occurrence of construction wastes and contribute to the total manpower savings.

3.5.3 Logistics 3.5.3.1

Protection

There should be adequate protection measures to prevent the need for unproductive rectification works during transportation to site, loading and unloading of the precast components as well as handling and storage on-site before installation. Hence, more manpower effort is required for protection to prevent such potential damages.

36

3.5.3.2

3 Precast Construction

Transportation

Transportation must be well-coordinated, considering the allowable transportation timing and route in Singapore so that the large prefabricated components can be installed immediately without the need for storage space and waiting time. Hence, it is important to allocate enough buffer time for the delivery, particularly if the precast components are transported directly from the country of manufacturing. The delivery should be aligned with the production sequence to avoid stock piling resulting in insufficient space in the factory and delaying the fabrication process. Otherwise, it would become a critical activity and affect the schedule for subsequent activities. The access to construction sites must also be planned properly so that the precast components can be smoothly handed over to the location of the cranes and handling equipment for the subsequent lifting (Pan et al. 2007). Any delay could be detrimental as if weather conditions turn bad and the prefabricated components cannot be fitted into position, a proper space for storage is required which adds to the construction wastes. Moreover, the fabrication needs to be road worthy, that is sturdy to ship or withstand long distance travel by land and sea. Otherwise, additional effort would be required to touch-up the precast components on-site.

3.5.3.3

Lifting

In Singapore, the large and heavy precast components will be lifted to very high unlike other countries where the buildings are usually low-rise structures. Automation and mechanisation can help the contractor to deliver the building to completion at a much faster rate. The use of high capacity cranes allows the lifting of bigger and heavier precast components into position faster. High capacity cranes also allow crane operators to have a better view of the launching and position process, hence removing the need for a signaller on ground. Anti-sway technology could be incorporated to allow the large and heavy precast components to be fitted properly. There is the need to invest in such cranes to enable lifting of bigger components or contractors will have to use smaller components which require more connections and man-effort for the multiple erection. However, there is the need for tie back at every 40 m tower rise which increases the cost of deployment for high capacity cranes in Singapore. Such cranes are not worthwhile to invest or rent for the smaller contractors just to get some manpower savings. This means that it is more difficult for smaller contractors to eliminate wastes and reduce the manpower effort in their projects. As the cranes are very expensive, contractors should aim to maximise their use without overspecifying or under-specifying by considering the size and planning for the capacity needed, taking into consideration that construction sites are often congested. It is critical that the precast components are properly attached to the lifting frame so that they will not become lop-sided during the hoisting process. This is because there will be construction downtime as the precast components have to be hoisted down, adjusted and lifted again.

3.5 Considerations During the Process of Precast Construction

37

Additionally, contractors all over the world are exploring the idea of robots assembling building components in pre-programmed patterns to replace labour-intensive and inefficient construction activities in the hope of automating the entire building process. Robots are also being developed to perform the role of quality inspection and for high ceiling and wall painting applications. For painting of building facades, the workers do not have to be on the gondola, eliminating the risk of having to work at heights which involves numerous processes to get the permit-to-work which adds to the construction wastes.

3.5.4 Installation 3.5.4.1

Construction and Project Management

Contractors need to plan, monitor, and control the execution of work effectively for optimal manpower deployment to reduce as much construction wastage as possible. A practical sequence of construction operations is required by considering the work packages and the availability of manpower and materials on site. The construction schedule should be updated periodically based on the actual progress and the 3D models of the weekly tasks can be printed out and displayed at the site notice board. Everybody would then have an overview of the entire works and possibly raise up interference and conflicts, if any, as the domino effects of delays by one activity could be significant on the full program. Industry practitioners said that contractors are generally good at understanding what needs to happen in the next two to three months but what needs to happen the next week or two are often overlooked. This is because their interest is in getting the job done in accordance with the contract. If the daily work is not finished, this should be updated so that the project timeline can be revised accordingly, and the contractor can assess if there is any impact to the critical paths and micro-plans. This is especially critical as unforeseen events at the construction site are inevitable and contractors will need to be able to anticipate and react quickly. While the design of simple-to-construct details and connections should be the task of all designers, the complexity of construction operations is difficult to determine without extensive site experience. However, contractors tend to stick to familiar people and teams rather than look for the best people for each job. There is also a mismatch between the demands of the construction sector and the capabilities of the available workforce which makes implementing precast construction challenging even till today. This suggests that construction firms and workers need to continuously reskill and train to use the latest equipment and digital tools to assuage the concerns of the clients they serve. There is also added difficulty for the contractor to supervise construction workers as many works are carried out concurrently. It is important for the contractors to fully understand the challenges and working conditions to be clear about how the assembly will work, and particularly how the different trades and disciplines will coordinate (BCA 2016).

38

3.5.4.2

3 Precast Construction

Building Information Modelling and Virtual Design and Construction

The Virtual Design and Construction (VDC) process helps integrate design, prefabrication, and construction, to identify upstream design clashes and simulate downstream construction workflow before the actual on-site construction. VDC can also weed out unsafe design and construction sequence before work commences (Li et al. 2012). Design changes are disparate, fragmented, and laborious to upkeep. There is a need for collaborative technologies, in which everyone involved in the project has access to the same information so that the various stakeholders can work together to ensure real-time information exchange, resulting in effective decision-making. A longer time is required during the front-end design stage for the virtual construction to reap the benefits of optimising manpower resources with minimal abortive works. Enabled by Building Information Modelling (BIM), VDC can potentially reduce construction wastages and optimise resources through the “right first time” mentality. BIM is a process involving the generation and management of digital representations of buildings. Utilising advanced 3D computer modelling technology, BIM allows building professionals of all disciplines and contractors to collaborate, network and exchange building information throughout the process of upfront planning, design, construction, and maintenance. Contractors can also align their cost strategy to BIM to produce very accurate bills of quantities and forecasts, which are then coupled together to build sequencing. This can be used to control suppliers to site and to limit materials delivery to improve the overall flow. From 1st July 2015, BCA has mandated the BIM electronic submission for building projects with GFA of at least 5000 m2 . This 3D visualisation is a big departure from the past where traditionally, building professionals communicate using 2D drawings. Often, rework and changes were retrospectively included in the 2D drawings. If this happens for precast construction projects, drawings that have been sent to the precaster would not be accurate and there will be construction wastes such as additional moulds required to accommodate the changes or redundant precast components that have been produced. Hence, the use of BIM is vital to resolve the complex design issues, ensure that all interfaces and details were resolved prior to production to get a precision fit (Rausch et al. 2016). BIM coordination of the precast joints to be installed on site is also a key component to ensure accurate alignment and prevent reworks. The progress of each precast component being installed can also be tracked and reflected in the BIM model in real-time. On top of that, there are many different consultants and subcontractors feeding into the BIM model and hence, it is hard to coordinate. The complexity and scarcity of knowledge prevented them from using BIM to help them execute precast construction projects which resulted in information silos as projects progress. Beyond the mandatory regulations, the study by Teo et al. (2015) found that the construction industry is not proactive in promoting the use of BIM at a higher level. Despite many years into BIM implementation, Singapore still face the same hurdles as encountered universally to fully realise the potential of the BIM technology.

3.5 Considerations During the Process of Precast Construction

39

The challenge is to change the traditional mind-set of building professionals and culture in the construction industry towards the benefits of using BIM. It is often the case that the contractors are engaged late in the project design phase and by this stage many of key decisions which affect how the construction will be done have been made. There is wasted effort to redo and input the construction details in BIM. In most construction firms, there is a lack of network infrastructure to allow simultaneous collaboration across the various disciplines such that all parties can work on a design concurrently and changes in one area will be reflected across the other disciplines, avoiding reworks which incur more manpower effort.

3.5.4.3

Info-Communications Technology

Info-Communications Technology (ICT) can be used throughout the construction process to anticipate issues and solve problems using data analytics, predictive analytics, data mining, and the Internet of Things to further optimise manpower usage. For example, logistics planning can be simulated to predict potential delays and smoothen logistics process. The biometric authentication system is already inplace to collect daily on-site manpower data for the respective trades. This have helped the contractors to manage the number of manpower on-site to prevent overstaffing or understaffing from happening, and to have visibility of workers to know what they are doing and whether there is a need to redeploy them. Riding on ICT to become a smart nation, Singapore has developed cranes that could be controlled remotely without the need for a crane operator to be seated in a cabin high above the ground (NTU 2016). Manpower effort could be optimised as the system calculates the optimal lifting path and each part that arrives on site and hoists into place can be transmitted into a digital database and integrated into the BIM model instantly. This is because workers do not need to manually record each part for site logistics and inventory checking which is very labour-intensive. ICT solutions can also be used for project management, materials tracking, defects tracking and tracking worksite safety hazards (Gambatese et al. 2017). Despite the capabilities of ICT solutions, the construction industry is still slow in using such technologies to eliminate wastes and reduce the reliance on labour.

3.5.4.4

Critical Inspections and Quality Checks

To provide an extra layer of quality control, there should be a suite of critical inspections and quality checks which must be completed and signed off before moving on to the next process within precast construction. Contractors tend to disregard this step as additional time is required. However, sufficient inspections and quality checks are required to ensure that the works are performed correctly and smoothly to avoid damage to work by subsequent operations and return visits by trades. The importance of construction quality is hence pivotal to minimise construction wastes and reduce the total manpower required.

40

3 Precast Construction

3.6 Gaps in Current Research With the potential for the universal growth of DfMA, the lack of considerations during the process of precast construction should be addressed so that construction wastes can be reduced and the utilisation of manpower can be streamlined. The Singapore construction sector needs to address the above considerations so that they can deliver precast construction projects competently, taking all reasonable steps to control and minimise the construction wastes as summarised in Table 3.4. Consequently, the total manpower effort required, both on-site and off-site, throughout the design, Table 3.4 Construction wastes in precast construction incurring more manpower effort Construction wastes

Sources

Causes

Defects and rework

Doran and Giannakis, Defects and rework 2011; Gao et al. 2018; due to errors in Lawson et al. 2014; design Lee et al. 2007; Lee and Kim 2017; Molloy et al. 2012; Panwar et al. 2015; Rausch et al. 2016; Staib et al. 2013

Defects and rework due to non-conformance

Precast construction considerations (Refer to Section) • 3.5.1.1 Early contractor involvement • 3.5.1.2 Standardisation, simplification and single integrated elements • 3.5.1.3 Interfacing coordination and connection • 3.5.1.4 Alignment and construction tolerance • 3.5.1.5 Accessibility for assembly • 3.5.4.2 Building information modelling and virtual design and construction • 3.5.1.4 Alignment and construction tolerance • 3.5.2.3 Total quality management • 3.5.2.4 Human resource management • 3.5.3.1 Protection • 3.5.4.4 Critical inspections and quality checks (continued)

3.6 Gaps in Current Research

41

Table 3.4 (continued) Construction wastes

Sources

Causes

Precast construction considerations (Refer to Section)

Defects and rework due to changes

• 3.5.1.1 Early contractor involvement • 3.5.1.2 Standardisation, simplification and single integrated elements • 3.5.1.6 Design approvals • 3.5.4.2 Building information modelling and virtual design and construction

Overproduction

Doran and Giannakis 2011; Heravi and Firoozi 2017; Lee et al. 2007

Early production of elements before they are needed

• 3.5.2.1 Factory location and capacity • 3.5.4.1 Construction and project management • 3.5.4.3 Infocommunications technology

Waiting and idle time

Heravi and Firoozi 2017; Lee et al. 2007; Molloy et al. 2012; Panwar et al. 2015; Yin et al. 2014

Waiting for sending elements to construction site and at the construction site

• 3.5.2.1 Factory location and capacity • 3.5.3.2 Transportation • 3.5.4.1 Construction and project management

Waiting for approvals • 3.5.1.6 Design approvals • 3.5.4.2 Building information modelling and virtual design and construction Waiting for inspection of elements

• 3.5.2.3 Total Quality Management (continued)

42

3 Precast Construction

Table 3.4 (continued) Construction wastes

Sources

Non-utilised resources Pan et al. 2007; Yin et al. 2014

Causes

Precast construction considerations (Refer to Section)

Poor utilisation of • 3.5.4.1 Construction workforce time and and project talent due to jobs and management skill mismatch Poor utilisation of workforce time and talent due to insufficient training

• 3.5.2.4 Human resource management

Transportation

Heravi and Firoozi 2017; Hwang et al. 2018; Lawson et al. 2014; Pan et al. 2007; Rausch et al. 2016; Romano 2003

Unnecessary transportation of equipment and materials

• 3.5.1.2 Standardisation, simplification and single integrated elements • 3.5.2.1 Factory location and capacity • 3.5.3.2 Transportation • 3.5.3.3 Lifting

Inventory

Doran and Giannakis 2011; Gambatese et al. 2017; Lee et al. 2007; Panwar et al. 2015

Excessive materials more than planned requirements, consuming floor space

• 3.5.2.2 Plant and machinery capabilities • 3.5.4.1 Construction and project management • 3.5.4.3 Infocommunications technology

Elements undergoing • 3.5.2.3 Total quality inspection, management increasing lead time Motion

Pan et al. 2007; Rausch et al. 2016; Romano 2003; Staib et al. 2013

Unnecessary • 3.5.3.3 Lifting movements of • 3.5.4.2 Building equipment, materials information and staffs due to modelling and inappropriate site virtual design and layout construction • 3.5.4.3 Infocommunications technology (continued)

3.6 Gaps in Current Research

43

Table 3.4 (continued) Construction wastes

Sources

Causes

Precast construction considerations (Refer to Section)

Extra-processing

Gambatese et al. 2017; Hwang et al. 2018; Lawson et al. 2014; Lee and Kim 2017; Li et al. 2012; Rausch et al. 2016; Staib et al. 2013; Yin et al. 2014

Unnecessary processes leading to wastes of materials and equipment

• 3.5.1.1 Early contractor involvement • 3.5.1.2 Standardisation, simplification and single integrated elements • 3.5.1.3 Interfacing coordination and connection • 3.5.1.5 Accessibility for assembly • 3.5.2.3 Total quality management • 3.5.4.1 Construction and project management • 3.5.4.3 Infocommunications technology

Note The list highlighted the more pertinent sources and commonly encountered construction wastes in precast construction that incurred more manpower effort. This will be used in the Survey Questionnaire as elaborated in Chap. 6

production, logistics and installation stages should reduce. This will also motivate contractors to consider the practicability of precast construction with full awareness of the risks and complexities involved to develop countermeasures and implement it in their projects.

Chapter 4

Lean Construction Implementation

4.1 Overview Lean first emerged in the construction industry back in the 1980s after it had gained full acceptance in the West, particularly the US and Europe, because of the dramatic improvement to their manufacturing operations. The roots of lean rests on production management principles developed by Toyota in the 1950s which provided major competitive advantage to Japanese manufacturing companies. The Toyota Production System (TPS) applied precast construction principles to aid in their processes to create a leaner organisation. Since then, lean production practices became a necessity for companies, including those from the construction sector, to improve their performances. Precast construction supports the advancement of lean as construction wastes are exposed throughout the design, production, logistics and installation. However, the construction wastes identified in Chapter Three showed that contractors in Singapore have not reached beneath the surface of lean management to the real foundation of Toyota’s success. Hence, this chapter reviews the literature on the Toyota’s story, the challenges of transferring the lean principles to the construction industry and the differences between issues in the construction and the manufacturing industry will be discussed. This chapter addresses the difficulties during the process of precast construction by exploring how prefabrication can be developed and managed with lean construction implementation.

4.2 The Toyota Story Today, the Toyota Motor Corporation is one of the largest multi-national automakers headquartered in Japan. Alongside other big corporations in the automotive industry such as Ford Motor Company (Ford) and General Motors Company, Toyota have © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_4

45

46

4 Lean Construction Implementation

made a remarkable impact based on their sales volume, profits, and production output since it was founded in 1937 by Kiichiro Toyoda. His father, Sakichi Toyoda, had foreseen that power looms would become yesterday’s technology while automobiles were tomorrow’s technology (Liker 2004). Sakichi Toyoda wanted him to make his mark to complete something that will benefit the world and hence, tasked him to start building the car business in 1930. Sakichi Toyoda is a well-known inventor, whose approach to making his power looms work evolved into a broader system that became part of the foundation of the Toyota Way. As a spinoff from Toyoda Automatic Loom Works set up in 1918, Toyota was established based on Sakichi Toyoda’s philosophy and management approach, as well as Kiichiro Toyoda’s beliefs of the need to strengthen their manufacturing excellence. In 1933, Kiichiro Toyoda tasked his younger cousin, Eiji Toyoda, to set up a “car hotel” which refers to a large parking garage to research machine tools, service Toyota products and liaise with other companies for supplies (Liker 2004). Similarly, Eiji Toyoda valued the company’s vision in contributing to society and learnt by doing. The Toyoda family leaders went through the growing pains of starting a company from scratch and shaped the development of the TPS. TPS was also the hard work of Taiichi Ohno, who was then Toyota’s plant manager, when Eiji Toyoda assigned him to match Ford’s productivity at a time when the Japanese were rebuilding their nation following the end of World War II in 1950. In the early years, Toyota built trucks manually just for the Japanese market. This primitive approach takes a long time and produces poor quality vehicles. At that time, Ford achieved short lead times and high quality in their manufacturing process. This is because Ford had the funding and large international market to support their mass production system which was designed to make huge quantities of a limited number of models. Subsequently, Ford encountered many unexpected events such as machine downtime, defective parts, and supplier problems, causing them to be unable to produce what was scheduled (Liker 1997). In contrast, Toyota needed to improve her manufacturing process by producing low volumes of different models to cater for consumer demand within the available resources. Ford emphasised on creating continuous material flow throughout the manufacturing process, standardising processes and eliminating waste. This was supposed to be the key enabler of Ford mass production’s success but a study by Toyota’s leaders revealed several imperfections in Ford’s mass production system. Ford’s mass production system creates waste that takes up inventory space and requires a high capital cost for dedicated assembly lines for one type of vehicle. There was uneven flow as the large batches of products that wait in the inventory could be defective and were unnoticed for weeks (Liker 2004). Further, if Toyota is not able to sell off their vehicles fast enough, there would be excess inventory and this poses a high risk as they may be stuck with obsolete inventory. To achieve a significant breakthrough and gain a competitive advantage in the automotive industry, Toyota began their quest to implement a system of one-piece flow that can create real flexibility for them to make what consumer wants. Toyota arranged machines to match the sequence in which they were used in the manufacturing process, so that products could flow in smaller lot sizes, individually from

4.2 The Toyota Story

47

one machine to the next (Black 2008). To create flow and minimise exposure of any inefficiencies, Toyota kept processes close together and ensured that materials move through processes without interruption. Toyota built-in the pull system concept at every segment of the manufacturing process, triggering the next step once the previous step is completed or met certain conditions that requires the process to continue. Subsequently, this idea evolved into the just-in-time (JIT) mechanism which allows Toyota to deliver the right items at the right time in the right amounts and accommodate the day-by-day shifts in consumer demand (Liker 2004). Initially, Toyota’s quality enhancement efforts are mainly short-lived as the measures are either preventive, which is carried out to deter its occurrence, or corrective which is performed to reduce its recurrence. Undoubtedly, preventing problems from being passed down the production line is much more effective and less costly than inspecting and repairing quality problems. Preventive and corrective measures are ineffective due to the absence of predictive measures to fully eliminate the root cause of the problem. Hence, Toyota decided to make use of Sakichi Toyoda’s invention which has a special way to automatically stop a loom whenever a thread broke. This mistake-proof mechanism is required to positively impact upon productivity and quality by reducing the amount of rejects and reworks to attain higher sales volume and profit maximisation. In a world of rapid change and great uncertainty, consumer needs and obsolescence happen very fast. Toyota understood that simple improvement to the current designs will not be able to retain support from customers. Toyota’s leaders borrowed the lessons of Edwards Deming, the quality guru, and recognised the need to continuously improve and innovate to stay ahead of trends in the market. The basis of continuous improvement is from Deming’s Plan-Do-Check-Act (PDCA) Cycle which strives to eliminate waste that adds cost without adding to value. Toyota challenged their staffs to propose ideas and come up with substantive solutions, one that has been considered thoroughly and not just a concept idea without any upfront planning and due diligence done. Realising the need to capture the luxury market as a new sales channel, Toyota started developing Lexus in 1983 which was finally introduced in 1989. This shows that Toyota was not complacent and did not just replicate reliable and proven methods but considered new technologies and new approaches in the pursuit of continuous improvement. During the global recession in 1970s, Toyota’s financial condition deteriorated but their competitors were in a worse state. The Japanese industry had to downsize their staff strength and delay their expansion plans to focus on maintaining cash flow. Many factories were destroyed and work had to stop since suppliers were also affected and unable to deliver the required components, affecting productivity. Despite that, Toyota recovered significantly faster than their competitors, showing their ability to implement strategies quickly and cautiously even in the face of any crisis. Comparatively, other Japanese automakers’ sales growth was unstable and net profit was not making much improvement. Furthermore, Toyota’s imports started to threaten the Western domestic manufacturers. Strong and consistent profits are vital to encourage shareholders to continue to invest in the development of Toyota’s business, enabling it to acquire assets, meet

48

4 Lean Construction Implementation

long-term borrowings, update plant and equipment, and build up reserves for future contingencies without the cost and risk of borrowing funds for these purposes. During this period of uncertainties, Toyota moved aggressively to beat the competition and marketed with exceptional products that break the mould. The Japanese government credited the power of TPS for propelling them forward and suppliers in the automotive supply chain also viewed TPS as an exemplar. This has also led the West to apply TPS principles which involves the combination of DFM and DFA to improve productivity through design and process improvements. Toyota was successful in yielding superior performance at their operations in the US which showed that the TPS practices were not culturally bound to Japan and are transferable to other countries and organisations. As part of TPS, Park (1996) found that it is essential to subcontract some assembly work to aggregate demand and reduce cost. Some Japanese automakers such as Toyota and Mazda were in cooperation to standardise parts such that subcontracting firms could expand their production capacity, as well as motivated to spend on research and development (R&D) and implement TPS principles. However, Liker (2004) reasoned that most companies were not successful in adopting the TPS as it is a powerful philosophy that requires a deep and pervasive cultural transformation, more than just applying the set of tools and techniques. Overall, the long-term collaborative relationship between automakers and suppliers were insufficient and needs to be strengthened so that quality products could be delivered productively. Toyota took decades to instil the Toyota Way within the company and there are still room for improvement. At times, Toyota lost focus and did not abide by the traditional Toyota priorities and guiding principles. Toyota’s market share in the industry increased rapidly from 6.3% in 1980 to 13.38% in 2010 (Andrews et al. 2011). During this period of growth, Toyota’s increasing vehicle complexity compounded by increased numbers of models and expedited designs made it difficult for them to manage efficiently. Production facilities were strained, and the lack of experienced engineers resulted in a deterioration of product quality. Manpower shortages prompted Toyota to outsource some portion of work to contractors who did not have the required understanding for a successful implementation of TPS. To keep up with demand, Toyota began to depend on suppliers which were not as skilled as their traditional circle of partners in Japan. These suppliers were not able to predict all the factors that could influence the vehicle’s performance as they do not fully understand the environment. Hence, Toyota vehicles recalled increased sharply from 2003 to 2005 and continued to grow till 2012 (Kehr and Proctor 2016). The complicated, time-consuming, and cost-intensive maintenance, as well as after-service led to a decrease in appeal for Toyota vehicles. This shows that subcontractor partnership is very important. Yet, Toyota still won more quality and safety awards than any other automaker during the same period. Since then, Toyota regained their long-standing repute for reliability and durability. According to J.D. Power (2016) US Vehicle Dependability Study, Toyota and Lexus have been consistently dominating the quality and long-term durability rankings for the past three years. Further, the number of problems experienced over the past twelve months by original Toyota and Lexus owners of 2013 model-year vehicles are notably lower compared to the industry average. Defects in vehicles should not

4.2 The Toyota Story

49

be taken lightly as it poses a serious risk to drivers and pedestrians. Toyota’s success is due to their company-wide effort in quality management, involving everyone in the organisation to continuously improve, learn from their mistakes and adapt to the changing environment. Essentially, the culture in Toyota brought about customer’s confidence level in vehicles manufactured by them. In 1990, Womack et al. (1990) coined the term “lean production” to describe and disseminate Toyota’s methodology to manufacturing that emerged as the best in the world. From then on, this term was accepted and widely used by authors who studied Toyota (Adler1995; Kenney and Florida1993; Rinehart et al. 1997). Apart from the automotive sector, research into the adoption of lean practices began expanding into the aerospace industry as well as other manufacturing and service operations. It is observed that Toyota’s productivity grew in terms of value-added work and not based on the utilisation rate of manpower and machines as it is redundant if resources are used to track defective parts or transport overproduce parts to storage. Underlining all these trends and the noticeable advancement is the realisation of the importance of speed in the supply chain. Toyota believed that focusing on shortening lead time by eliminating waste in each step of a process leads to best quality, low cost, and on-time delivery, while improving safety and morale—known as QCDSM (Liker 2004).

4.3 Applying Lean in Streamlining Manpower The TPS is one example of the Toyota Way which has functioned effectively. Taiichi Ohno’s disciple Fuji Cho developed the TPS house as shown in Fig. 4.1 to serve as a guide to teach others why there is a need and how to bring all the elements together. The TPS house which represents a system with two pillars holding up a roof and a foundation are critical to understand the general approach of developing and improving the contractor’s lean production system. Lean is about how companies can remove waste and unnecessary non-value adding activities, so that they can be efficient, yet still provide exceptional value and high quality. Contractors can determine where the greatest opportunities to eliminate waste is by identifying the activity which takes up the most manpower in the entire process (Koskela 1992).

4.3.1 Just-in-Time JIT is a pull system which demands that the contractor know how to get their workforce to produce exactly what is needed, in the amount needed or at the rate at which the product can be sold and when it is needed. JIT is required to eliminate any wasteful situation such as overproduction, lack of standardised work, queue waiting time, transportation and handling, inventory, unnecessary motions, defective products and underutilised skills. The JIT mechanism requires a moving continuous-flow

50

4 Lean Construction Implementation

Fig. 4.1 The TPS house. (Source Gao and Low 2014)

assembly line where the relationship between flow time and installation demand fits one another. In certain circumstances, a continuous one-piece flow is not feasible and batch production has to be implemented. Batch production is not ideal even if there is capacity and fewer deliveries because the rest of the lot will have to wait while the first few precast components are being worked on. When the lot is transferred to the next process, it is too late to provide feedback to the upstream process on the quality of parts in that batch. It is thus recommended to produce parts in small batches as far as possible so that quality problems could be detected quickly and corrected before large inventories of defective parts are produced. The costs of inventory, loss of immediate feedback, higher tendency of hidden problems in larger quantities are deemed to be more important than the benefits of economy of scale and having large inventory buffers in the event of equipment failure. Moreover, to link production to the customer by matching the pace of production to the pace of actual final sales, takt time should be recorded. Takt times is the maximum amount of time the prefabricated component needs to be completed to match client’s demand. This will be extremely useful when growth slackened or when customers’

4.3 Applying Lean in Streamlining Manpower

51

needs were diversified such that the demand becomes less than supply. Therefore, it is best to design minimum lead-time production system to manufacture the precast components with efficient manpower usage.

4.3.2 Levelled Production The peaks in the volume of precast components and mix should also be levelled to allow the pattern of production to follow the pattern of installation. This strategy known as heijunka, makes the most efficient use of people and equipment, steadying the workload in all processes. Levelled production also prevents a disproportionate burden from being imposed on one team or one type of machinery while others are idle or lightly loaded. The precaster and the contractor should coordinate and have a firm and reliable schedule for the next month at least ten days in advance (Liker 1997). In this way, inventory can be controlled and minimise construction wastes. The precasters should also work closely with their suppliers to achieve high quality prefabricated components efficiently. They should secure long-term partnerships with only a few reputable suppliers. This allows information sharing to take place so that suppliers also know the technical details of other components and consider if there is need to improve their manufacturing process and enhance the interoperability with other components to produce a better product.

4.3.3 Jidoka To prevent defects from travelling any further into the system, the jidoka principle of automatically stopping the machine work whenever an abnormality occurs must be adhered to. When the production line is halted as soon as there is a problem, it is easier to identify the causes and work out the solution. Workers need not watch machines run to detect abnormalities and have the time to do more value-added activities. This includes analysing how the problems can be solved and finding new ways to streamline manpower and eliminate waste. The Singapore National Productivity Board (1993) pointed out that a critical success factor in manufacturing is the commitment to defect-free quality work by every worker. Every worker should ensure that no error is ever repeated which can be realised by using the “Five Why’s” to trace each error to its ultimate source. Asking “why” five times is a root cause analysis method done to dig deeper and grasp the entire situation to figure out the best way to tackle the problem. Problems occurring from the interaction between processes are high and harder to resolve when they have gone beyond the respective stages of the production system. Inspection should also be performed on a representative sample basis. The checker must know exactly what should be done at these processes and what constitutes a mistake. However, sample inspection will not be able uncover all problems in

52

4 Lean Construction Implementation

every process and by then rework is inevitable, causing wastes and higher cost of production. If mistakes made early in the process are not corrected and subsequent work proceeds, there will be a compounding effect as work that comes later hides the mistake and prevents access to the mistake for correction. Quality must be builtin rather than trying to inspect it after. The effective strategy should be to design systems to find and fix mistakes before they turn into defects and not to be good at catching the defects (Black 2008). Those workers involved in the upstream processes should be made known about their mistakes and fix it themselves. This is because if the downstream process fixed defects made upstream, there is no incentive for those upstream to correct their mistake and eliminate defects. This will result in high occurrence of construction wastes and inefficient utilisation of manpower.

4.3.4 Visual Management To minimise paperwork and eliminate the need for human intervention which is prone to errors, the kanban system can be used. It is a tool which allows team members and workers to quickly identify and resolve abnormalities in a product or production process before the article passes to the next process. Every precast component that flows through the production system will carry its own kanban such as printed cards and will be removed once it has been used or sent back to the preceding process as orders for additional components. Kanban is necessary to maintain synchronisation of the various processes and illuminate even hidden problems that affect the overall efficiency of the production system. If there is no kanban, production should be restricted and not build up inventory. Furthermore, visual indicators and signals such as coloured lights, reader boards and audible tones can help workers to track the production progress and keep production on schedule. This will also equip team members with the ability to discover and solve problems in real time, and reduce costly out-of-sequence work if there is a need for rework. However, kanban is only suitable for parts that are needed repeatedly and for companies that have established a continuous flow and kaizen. Kanban is not suitable if every item can be produced in one space because everyone is able to see when the next process needed supplies.

4.3.5 Stable and Standardised Process The concept of Six Sigma which aims to achieve 3.4 defects per million opportunities should be pursued so that the precast construction is near-perfection such that abortive works incurring more man-effort is not required. Six Sigma can be categorised as a subset of lean as it focuses on fixing individual processes while lean fixes the connections among processes. Six Sigma provides a consistent framework for performing work to designated times and identifying opportunities for maintaining,

4.3 Applying Lean in Streamlining Manpower

53

monitoring and improving work procedures (Worley and Doolen 2015). By doing so, team members can address the client’s every concern promptly and enable workers to operate in an environment such that the precast components can be assembled efficiently. With standardised work, best practices can be assured and the current best practices can become the baseline for further improvement. This involves training and inculcating good habits and having everyone practise them, thus encouraging the continuity of good habits to further reduce construction wastes and streamline manpower.

4.3.6 Continuous Improvement Theoretically, lean implementation begins with leadership commitment and is sustained with a culture of continuous improvement. The belief is that contractor can always find more waste to cut away and contribute to optimising manpower. This is a kaizen cycle which will be repeated for tracking and evaluating the product performance in each step of the way. The aim is to find out how the root of the problem can be solved and not attempt to hide it or use other solutions to rectify the defects which is a waste of time. However, contractors may resist efforts towards kaizen as they are more interested in new developments which are more recognised or viewed as more value-adding. Contractors also tend to only manage the day-today activities rather than lead their people to achieve long term objectives and do not place emphasis on the means to achieve the results (Russell and Stouffer 2003). This would result in insufficient problem-solving capability for present products and processes. In fact, both must take place simultaneously. Big improvements take years of work and it is important not to get frustrated or disillusioned and giving up too soon. The people to drive continuous improvement should come from within the company as they would be in the best position to understand the company’s condition and vision. Toyota has in place a suggestion program based on the premise that people inherently want to improve their work environment, and that the contributions of every employee provide long term continuous improvement. There were high levels of participation and this has led to greater job satisfaction as team members and workers have a sense of ownership and able to control what should be done even on what is perceived to be small or unimportant ideas. Black (2008) does not support the idea of hiring external consultants to come out with the correct strategy based on data given to them. The role of external consultants should only be limited to those areas where the company does not have the expertise in. This is because the external consultants may not necessarily have construction knowledge but are only experts in thinking lean and streamlining processes. The drive for continuous improvement should be executed from the top management who should talk to staffs and understand their needs. It will be a morale boost for people to see management getting involved too (Black 2008). The management must learn to embrace a long-term view, with the consciousness that what is being done

54

4 Lean Construction Implementation

today is part of a continually improving process. They should walk the ground, identify areas for improvement and request the supervisor to investigate the matter immediately. Often, they are overloaded at work and overwhelmed with numerous meetings that they fail to engage with their team, ensuring that they stay invested and fully committed to contribute to the overall project goals. The top management can form a dedicated team to focus on running kaizen efforts, train people and make sure all the follow-up work is done. This team should help to ensure alignment across the organisation, audits of implementation and results, replication of best practices and standardisation of work. The team is akin to a Quality Control Circle (QCC) where a group of internal people come together and go through the PDCA Cycle on a full-time basis. It is critical to select suitable members to join this team as each member must not only take care of their portion but also have the foresight to assess how their portion will affect subsequent processes. It is also important that the team collect feedback from their partners and suppliers and assess if there is a need to change and how continuous improvement can be worked into their company. Any change should begin from a justifiable need and adequate buy-in. This enables improvements to be made quickly and requires active communication among the different stakeholders who should not only be interested on their individual processes. As circumstances, employees’ experience and methodologies change, continuous improvement programs must also evolve over time. To generate new inputs and bring in fresh outlooks, employees in this dedicated team should rotate every few years. This will give other employees the opportunity to master lean thinking and allow the lean mind-set to diffuse throughout the organisation over time. This approach agrees with Toyota’s success of learning by doing kaizen, not just reading about it to result in greater manpower savings. This is because people will be motivated to perform better and enjoy from the reduced workload or removal of wastes, giving them both a sense of accomplishment and job satisfaction. Consequently, the internal culture of the company will be rejuvenated. Ultimately, every contractor must find its own way and apply the TPS such that the centrality of people is at the core to continuously improve the processes and ensure that non-value-added wastes are removed to streamline manpower usage.

4.4 Lean Production to Lean Construction Lean production is based on the Toyota Way’s four broad principles—Philosophy, Process, People and Problem Solving as shown in Fig. 4.2. Lean production was developed to “half the human effort, half the physical space, half the investment tools, half the engineering hours and half the lead time to develop new products” (Womack and Jones 2003). Similarly, lean in a construction context should give contractors a substantial advantage over their non-lean-based competitors. There have been various definitions of lean construction but the central theme is that lean construction is a way of designing production systems to minimise wastage of materials, time, and

4.4 Lean Production to Lean Construction

55

Fig. 4.2 Toyota way model. (Source Liker and Meier 2006)

effort to generate the maximum possible amount of value for the client (Best and De Valence 2002; Salem et al. 2005). This is achieved by minimising activities that do not add value to result in manpower savings. The Toyota Way suggests the need to understand the primary philosophy, necessitate each process, get the right people, apply problem-solving methodology, and measure the overall result as summarised in Table 4.1. When moving from manufacturing production activities to applying lean principles in the construction industry, enhancing value and eliminating waste becomes more complex (Tommelein 1998). The transfer of lean production technology from the manufacturing to the construction industry has its limits. Since manufacturing production is carried out under factory-controlled conditions, it is easy to see the product flowing along the production line, making it easy to identify the processes, main steps, and constraints. Further, every manufacturing activity for different projects is almost the same and only minor fine-tuning is required. Manufacturing outputs consist of precisely engineered individual parts that are produced in large numbers and with very little variation. In the construction industry, production numbers are much lower and components are numerous and wide-ranging as each construction project has unique physical, environmental, or social characteristics. There is a far greater variety of processes, materials, trades, and specialists in construction than in manufacturing. There is the need to deal with more complex issues such as the relationship between concurrent activities, weather, the size, and type of components being produced amongst other factors (Choy and Ruwanpura 2006). In construction, the many discrete phases involving different professionals makes it tough to make things right the first time. For construction works, there is absolutely no room for error as the time and cost that will be involved for reworks are massive. Construction duration are usually

Use “Pull” Systems to Avoid Overproduction

3

(continued)

“The more inventory a company has, …the less likely they will have what they need.”—Liker (2004, p. 104)

Create Continuous Process Flow to Bring Problems to the “If some problem occurs in one-piece flow manufacturing Surface then the whole production line stops. In this sense it is a very bad system of manufacturing. But when production stops everyone is forced to solve the problem immediately. So team members have to think, and through thinking team members grow and become better team members and people.”—Liker (2004, p. 87)

2

Process

Base Your Management Decisions on a Long-Term “The most important factors for success are patience, a Philosophy, Even at the Expense of Short-Term Financial focus on long-term rather than short-term results, Goals reinvestment in people, product, and plant, and an unforgiving commitment to quality.”—Liker (2004, p. 71)

Important quotes from the past and present Toyota’s management

1

Principle No. Principle

Philosophy

Broad principle

Table 4.1 Toyota way management principles

56 4 Lean Construction Implementation

Broad principle

Table 4.1 (continued)

Level Out the Workload (Heijunka)

Building a Culture of Stopping to Fix Problems, to Get Quality Right the First Time

4

5

Principle No. Principle

(continued)

“…no problem discovered when stopping the line should wait longer than tomorrow morning to be fixed. Because when making a car every minute we know we will have the same problem again tomorrow.”—Liker (2004, p. 128)

“Levelling the production schedule may require some front-loading of shipments or postponing of shipments and you may have to ask some customers to wait for a short period of time. Once the production level is more or less the same or constant for a month, you will be able to apply pull systems, and balance the assembly line. But if production levels—the output—varies from day to day, there is no sense in trying to apply those other systems, because you simply cannot establish standardised work under such circumstances.”—Liker (2004, p. 113)

Important quotes from the past and present Toyota’s management

4.4 Lean Production to Lean Construction 57

Broad principle

Table 4.1 (continued)

Standardised Tasks are the Foundation for Continuous Improvement and Employee Empowerment

Use Visual Control so No Problems are Hidden

Use Only Reliable, Thoroughly Tested Technology that Serves your People and Processes

6

7

8

Principle No. Principle

(continued)

“Society has reached the point where one can push a button and be immediately deluged with technical and managerial information. This is all very convenient, of course, but if one is not careful there is a danger of losing the ability to think. We must remember that in the end it is the individual human being who must solve the problems.”—Liker (2004, p. 159)

“…you must clean up everything so you can see problems…complain if he could not look and see and tell if there is a problem.”—Liker (2004, p. 149)

“For a production person to be able to write a standard work sheet that other workers can understand, he or she must be convinced of its importance…High production efficiency has been maintained by preventing the recurrence of defective productions, operational mistakes, and accidents, and by incorporating workers’ ideas. All of this is possible because of the inconspicuous standard work sheet.”—Liker (2004, p. 140)

Important quotes from the past and present Toyota’s management

58 4 Lean Construction Implementation

People and partners

Broad principle

Table 4.1 (continued)

(continued)

Respect Your Extended Network of Partners and Suppliers “Toyota is more hands-on and more driven to improving by Challenging Them and Helping Them Improve their own systems and then showing how that improves you…Toyota will do things like level their production systems to make it easier on you…There is more opportunity to make profit at Toyota. We started with Toyota when we opened a plant with one component, and as performance improved, we were rewarded, so now we have almost the entire cockpit. Relative to all car companies we deal with, Toyota is the best.”—Liker (2004, p. 199)

11

“Until senior management gets their egos out of the way and goes to the whole team and leads them all together…senior management will continue to miss out on the brain power and extraordinary capabilities of all their employees…”—Liker (2004, p. 171)

Develop Exceptional People and Teams Who Follow Your “Respect for people and constant challenging to do Company’s Philosophy better—are these contradictory? Respect for people means respect for the mind and capability. You do not expect them to waste their time. You respect the capability of the people…Mutual respect and trust means I trust and respect that you will do your job so that we are successful as a company. It does not mean we just love each other.”—Liker (2004, p. 184)

Grow Leaders who Thoroughly Understand the Work, Live the Philosophy, and Teach it to Others

Important quotes from the past and present Toyota’s management

10

9

Principle No. Principle

4.4 Lean Production to Lean Construction 59

Principle No. Principle

Go and See for Yourself to Thoroughly Understand the Situation (Genchi Genbutsu)

Make Decisions Slowly by Consensus Thoroughly Considering All Options; Implement Rapidly”

Become a Learning Organisation Through Relentless Reflection (Hansei) and Continuous Improvement (Kaizen)

12

13

14

Broad principle

Problem-solving

Table 4.1 (continued)

“We view errors as opportunities for learning. Rather than blaming individuals, the organisation takes corrective actions and distributes knowledge about each experience broadly. Learning is a continuous company-wide process as superiors motivate and train subordinates; as predecessors do the same for successors; and as team members at all levels share knowledge with one another.”—Liker (2004, p. 250)

“If you have got a project that is supposed to be fully implemented in a year, it seems to me that the typical company will spend about three months on planning, then they will begin to implement. But they will encounter all sorts of problems after implementation, and they will spend the rest of the year correcting them. However, given the same year-long project, Toyota will spend nine to ten months planning, then implement in a small way - such as with pilot production—and be fully implemented at the end of the year, with virtually no remaining problems.”—Liker (2004, p. 237)

“Observe the production floor without preconceptions and with a blank mind. Repeat “why” five times to every matter.”—Liker (2004, p. 223)

Important quotes from the past and present Toyota’s management

60 4 Lean Construction Implementation

4.4 Lean Production to Lean Construction

61

tight and the contractor will have to pay liquidated damages if they fail to meet the stipulated time for completion. Hence, mock-ups and samples are usually done to ascertain the workmanship quality before full-scale construction. Opportunities for manpower savings are often loss as workers change frequently and there will not be any learning curve. Although precast construction can be used to eliminate manpower inefficiency and is a blood relative of lean, many contractors’ practices do not fit nicely with the five basic lean principles. First, the lean approach requires them to identify value from the client’s point of view, understand the client’s concerns and analyse holistically. In this aspect, contractors should institutionalise what causes the wastes throughout the precast construction process from the organisation structure and from work practices, and systematically drive it out to optimise manpower deployment. After gaining a better understanding of what is valuable to the client, contractors can proceed to map the value stream of the entire precast construction process and be committed to implement it. This is so that they can identify how to create better flow, eliminate non-value-added activities, and align with the subcontractors. The value stream mapping should ideally be done by working with the client upfront to understand the challenges that will be involved. Based on their experience and expertise, the contractors can advise the required changes to meet the client’s value and streamline manpower requirements. With the value stream mapped, contractors create flow to ensure that the client’s value can be seen throughout the precast construction process. This will remove construction wastes resulting in increased manpower savings as work progresses. However, this is tough as contractors need to manage a wide range of tasks which span across many disciplines. Within a fast-changing and increasingly complex construction industry, there is mounting pressure to do more with fewer people and less resources, not solely relying on precast construction but also the methodology of manging the entire construction process. This is valuable to the client and thus contractors should train and expose their team members to manage precast construction projects so that they gain in-depth knowledge and able to extend its use in future projects. To ensure the flow of benefits in the value stream, contractors should adequately control the amount of work and resources to reduce construction wastes. The establishment of an automatic pull process for the interaction between logistics and construction on site is key to optimise the entire flow and manpower effort in the process of finding ways to minimise any construction downtime.

62

4 Lean Construction Implementation

Lastly, lean construction seeks to attain the perfection of value-adding activities and the minimisation of non-value-adding activities by identifying areas of improvement (Womack and Jones 2003). By ensuring consistency and continuity in applying the lean construction methodology, the adoption of precast construction will be high and sustainable. The following will describe the precast construction process from the perspective of the fourteen Toyota Way management principles.

4.5 Precast Construction Process Shift Through Lean 4.5.1 Focus on Long-Term Results As the governing body, BCA has propagated their vision for the Singapore’s construction industry, that is, to build a highly integrated and technologically advanced construction sector led by progressive firms and supported by a skilled and competent workforce by 2020. Precast construction is one technology that construction firms, who are driven by business concerns, need to be convinced would be a good investment that can not only help to improve site productivity but also force significant manpower reduction. Contractors should think through the implications of implementing precast construction which is very different from the company’s regular approach and the effect of it on their partners and management style (Rao et al. 2014). With that, they should develop a long-term capability to adopting precast construction from design, production, logistics to installation. Rather than abandoning the idea of precast construction because results cannot be seen in the short term or deciding to proceed because results were seen in the short term, contractors should be patient. To do so, value stream mapping can be utilised to draw pictures that help contractors see linked chains throughout the precast construction process and identify construction wastes which can be removed. The purpose is to guide improvements based on the philosophy that there is a need to straighten out the overall flow of the value stream before deep-diving into fixing individual processes (Vrijhoef and Koskela 2000). Although improving isolated processes is easier than improving flow across value streams, it is not recommended as the consequence to the overall process may be detrimental. Individual processes just need to be stabilised to support the flow needed to give the clients what they want, in the amount they want, and when they want it. To focus on long-term results of eliminating construction wastes and reducing manpower effort, the end of the flow should be mapped out first (Rother and Shook 1999; Marhani et al. 2013). This is the current state map which is meant to explain the condition of the precast construction flow in the value stream, the inhibitors to the flow and understand the information flow process and the level of activity necessary

4.5 Precast Construction Process Shift Through Lean

63

to sustain it. At this stage, it is important to evaluate the processes thoroughly to know what the current obstacles are to serve as a basis to develop a future state map.

4.5.2 Create One-Piece Flow Based on the design, the man-effort required, material and information flow of all the work processes should be built to the demand of precast components required. This is the future state map which provides a high-level picture of the flow of material and information for subsequent refinements. The future state map should aim to create connected flow in the value steam that can produce any precast component at any time without any limitation. It is important that all aspects of the various disciplines such as architectural, structural and MEP are considered upfront. Problems can then be brought to the surface and everyone will be forced to solve the problem immediately to enable continual operations (Ogunbiyi et al. 2014). Individual processes must be able to produce consistent results, that is, the same quantity of quality products given the same amount of time and resources with a high degree of reliability (Al-Tahat and Jalham 2015). If these processes are not stable, it is difficult to identify construction wastes and begin the continuous improvement cycle. Process instability should be avoided by having repetitive floor plates and modules so that there will not be varying amounts of resources and processing steps (Liker 2004). With each different module, there should be a small buffer to destabilise the continuous flow as each process is dependent on the other in the entire precast construction workflow.

4.5.3 Use Pull-Replenishment The precast components should be built and supplied to site according to the takt time to minimise inventory storage space required. Takt time refers to the time in which the finished product has to be completed in order to meet the rate of it being demanded. The precaster should still maintain a considerable amount of inventory to ensure that they can fulfil the demand required at any point in time (Horman and Thomas 2005). From the contractor’s viewpoint, upfront detailed planning is required to determine how many and when to bring in the respective precast component and this is highly dependent on the speed of production.

64

4 Lean Construction Implementation

4.5.4 Level Out the Workload Contractor should group the same precast components that belong to a common value stream. This is called isolating variability which serves to balance the resources, assigning the necessary manpower, machines, and materials to attain process stability. Similarly, contractors should assign resources to a task in ways that are consistent with the amount of work available to perform to maintain low variability in labour productivity (Thomas et al. 2002). Team members should assign all workers with a task and not experience waiting time. This can be achieved by minimising component variability as there is no point in levelling the workload if majority of the processes cannot be standardised (Nahmens and Ikuma 2011).

4.5.5 Stop to Fix Problems Workers should have the practice to check the incoming work to ensure that it is free of defects and verify that their own work is free of defects before handing over to the next activity. This is so that construction wastes are not passed on to the next process, especially when works of different subcontractors need to integrate. With the connected flow, contractor will be warned to stop prior to complete system failure and take pre-emptive corrective action (Krafcik 1998; Torres and Olaya 2010). The interdependent processes will significantly increase the level of urgency to resolve any interruptions to the precast construction flow (Heravi and Firoozi 2017). Consequently, the next layer of issues in an ongoing cycle of continuous improvement will surface. As obstacles are being overcome in each successive loop in the continuous improvement cycle, construction wastes that are highlighted are expected to lessen resulting in manpower savings.

4.5.6 Standardise Tasks Without standardisation, the continuous improvement cycle will be wasted effort and work will return to the old way and manpower effort cannot be reduced (Lapinski et al. 2006). In Singapore, many construction firms have an internal quality management system and have also obtained external certifications such as the International Organisation for Standardisation (ISO) 9001 and Japan Quality Assurance Organisation. If developed and executed correctly, policies and procedures create a responsibility chain that ensures a smooth and standardised flow throughout the precast construction process (Jones et al. 1999; Song and Liang 2011). With precast construction, the 3S principles of Standardisation, Simplification and Single Integrated Element

4.5 Precast Construction Process Shift Through Lean

65

which underpins the buildability concept should be adhered to as it can help to reduce manpower downstream (Knaack et al. 2009). All the specific steps throughout the precast construction process should be carefully defined with the required performance and action party so that any deviation from the standard will be detected immediately (Terry and Smith 2011).

4.5.7 Visualise Process To streamline manpower and ensure quality, manual sample inspection should not be the sole means to visualise the process to tell if there is a problem. Contractors must move away from manual practices which are limiting the potentials of visualising the precast construction process. There should be a communication means that is able to tell at a glance how work should be done at the factory and construction site. Digitalisation is the way forward to complement humans in managing the precast construction process to create the most optimum environment to do a good job (Arayici et al. 2011; Dave et al. 2015). This requires transformations in the way the construction industry used to work, collaborate and share information to deliver the project and will ultimately result in manpower savings both on-site and off-site (Al-Ashaab et al. 2013).

4.5.8 Adapt to Operations To adapt their operations to precast construction, contractors need to take a fresh look at all related processes that will impact people in the long run (Greenwood et al. 2017). Contractors are to investigate what they can do to streamline manpower throughout the precast construction process and this should be driven by someone with operational responsibility such as the chief executive, supported by the middle manager and implemented by the people at the working level (Forbes and Ahmed 2010).

4.5.9 Empower Your People The construction industry relies on people to successfully implement engineering expertise, innovative products, and process technology (Amitha and Priya 2017). To make people ready to shift to precast construction, it is important for them to take ownership and contribute to the company’s goals to reduce construction wastes and

66

4 Lean Construction Implementation

manpower effort. Although there is a need to do more and in areas where they are not familiar with, it is vital that they are constantly challenged with meaningful work and encounter occasional pressure (Orr 2005). This will help to stimulate a workplace where people would be free to explore solutions to the problems that they themselves know best rather than staying complacent (Green 2002; Santorella 2016). As a result, there will be numerous inputs, contributing to the continuous improvement cycle. Furthermore, they will be able to effectively control problems and have someone taking up the responsibility whenever a problem occurs (Like and Convis 2012).

4.5.10 Develop Your People There is a need to enhance the knowledge and skillsets of team members and workers so that they can take on new roles in precast construction and ensure that the construction firm can keep pace with the technological advancement to remain relevant and emerge stronger. This can be done by training them to be multi-skilled and be familiarised with various operations so that the contractor has the flexibility of re-allocating them to another task or role whenever someone is not available (Spear and Bowen 1999; Thomas et al. 2003). Construction firms should encourage their people to be recognised for having competency in multiple construction trades to carry out more than one type of work tasks on site. This will reduce construction downtime as these multi-skilled workers can be re-deployed to take on another task instead of getting a new batch of workers to continue the works. In this way, they will become equipped with the engineering capability to suggest technical solutions, design and decide the various applications to reduce construction wastes (Terry and Smith 2011).

4.5.11 Grow Together with Solid Subcontractors and Suppliers The goal should be to eliminate wastes not only in their own firms but also in their suppliers and subcontractors as well as in the connecting processes to result in overall manpower reduction in a precast construction project. The precaster, main contractor, subcontractors and suppliers should collaborate, share risk and learn from one another (Achanga et al. 2006). The precaster, subcontractors and suppliers should have gone through a series of stringent evaluation to earn their spot into the partnership network

4.5 Precast Construction Process Shift Through Lean

67

of the main contractor (Maturana et al. 2007). Those who are doing a good job should not be let go because of cheaper alternatives as it is likely to result in more construction wastes. Having this belief is important to motivate their subcontractors and suppliers to improve continuously by also finding and eliminating wastes. Hence, the contractors should set high expectations and get all their suppliers to be aligned so that they can collectively apply precast construction and achieve QCDSM.

4.5.12 Observe and Understand the Process All the stakeholders should have a good understanding of the entire prefabrication process before starting off with their transformation process from traditional cast in situ to precast construction. They should have a clear understanding of how precast construction can help them achieve the desired outcome as well as how or why construction wastes occur to result in long term payoffs. They can apply the 80/20 rule of investing 80% of their energy on the 20% of problems that will yield 80% of the total benefit (Worley and Doolen 2015). With that, they will be able to understand the characteristics of the problem, seek out solutions and identify the construction wastes which can be removed. Apart from the construction wastes at the individual process level, it is also important to identify the subsequent parts which can yield significant improvements in overall manpower reduction (Holweg 2007).

4.5.13 Consider Alternative Solutions Alternative solutions should be considered throughout the precast construction process to verify the suitability and long-term effectiveness of the planned solution before implementing it. This approach of outlining the pros and cons of various options should be a standard practice at all levels of the construction firm and across all functions. A thorough evaluation and reflection will be able to help decide the course of action and align resources accordingly to result in construction wastes minimisation and manpower optimisation (Liker and Meier 2006).

4.5.14 Review Process The best way to understand construction wastes is to explore the ways in which the process and people interact and discover how and why people had to adapt and work around or were just out of process (Ghosh and Robson 2015). The contractor should target to consolidate waste activities to capture the maximum improvement and to

68

4 Lean Construction Implementation

continuously be on the lookout for problems before they occur. Hence, there is a need to develop a second current state map to understand where the contractor is at after the first future state map have been carried out. Thereafter, a second future state map should be developed. The comparison between current state value stream map and future state map provides a basis for identification of where improvement action might best be focused (Heravi and Firoozi 2017; Liker and Franz 2011).

4.6 Gaps in Current Research In 1999, the Construction Task Force in Singapore briefly mentioned about lean construction but it was not pursued. In 2015, the BCA International Panel of Experts for Productivity recommended that the construction industry considers lean practices to re-examine their processes and workflow. In 2016, BCA launched a new specialist diploma in lean construction which shows the importance of applying the lean methodology in the Singapore construction industry. The widespread applicability of lean principles have been justified by numerous researchers and the main points discussed were simply about the current conditions and future directions (Vrijhoef and Koskela 2000; Koskela 2017; Mostafa et al. 2016). Gao and Low (2014) studied about developing a Toyota Way model for lean implementation in the Chinese construction industry. Researchers have also discussed about incorporating and enhancing lean construction tools and techniques as current tools may not be adequate (Ballard and Howell 2003; Dave et al. 2016). Studies have also covered the barriers and benefits of lean construction, as well as applying lean for green and sustainability, safety, BIM, and labour productivity issues. This chapter represents the first attempt to showcase that similar benefits by applying lean principles could also be realised in precast construction, particularly in reducing construction wastes and streamlining the total man-days utilisation throughout the design, production, logistics and installation process as summarised in Tables 4.2 and 4.3.

Liker 2004

Lapinski et al. 2006

Koskela 1992

Horman and Thomas 2005

Holweg 2007

Greenwood et al. 2017

Ghosh and Robson 2015

Forbes and Ahmed 2010

Amitha and Priya 2017

Al-Tahat and Jalham 2015

Al-Ashaab et al. 2013

Sources

2

3

4

5

6

7

8

9

10

11

































































√ √

















Focus on Create Use Level Out Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers √ √

1

Table 4.2 Proposed lean implementation in precast construction 13

14













(continued)













Observe Consider Review and Alternative Process Understand Solutions the Process

12

4.6 Gaps in Current Research 69

2

3

4

5

6

7

8

9

10

11





√ √

√ √







Focus on Create Use Level Out Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers √ √ √ √ √ √

1

13

14







Observe Consider Review and Alternative Process Understand Solutions the Process

12

Note The list highlighted the main points to reduce construction wastes and manpower effort in precast construction from the more pertinent sources. This will be used in the Survey Questionnaire as elaborated in Chapter Six

Worley and Doolen 2015

Terry and Smith 2011

Ogunbiyi et al. 2014

Sources

Table 4.2 (continued)

70 4 Lean Construction Implementation

Overproduction due to oversupply of precast components resulting in the need for inventory

Production Stage

Defects and rework due to improper interfacing between precast components resulting in extra-processing

Extra-processing due to design changes

Defects and rework due to incompatibility of design with downstream precast construction processes

Design Stage

Key Construction Wastes in Precast Construction

2

3

4

5

6

7

8

9

10

11

















Focus on Create Use Level Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment Out the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers

1

Table 4.3 Mapping of key construction wastes in precast construction and relevant lean principles for total man-day reduction 12

13

14

(continued)

Observe Consider Review and Alternative Process Understand Solutions the Process

4.6 Gaps in Current Research 71

Waiting and idle time and transportation for the delivery of precast components across multiple sites

Logistics Stage

Non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

Waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

Key Construction Wastes in Precast Construction

2

3

4

5

6

7

8

9

10

11











Focus on Create Use Level Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment Out the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers √

1

Table 4.3 (continued) 12

13

14



(continued)

Observe Consider Review and Alternative Process Understand Solutions the Process √

72 4 Lean Construction Implementation

Defects and rework due to non-compliance to quality requirements of precast construction

Non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

Installation Stage

Motion from the arrival of the precast components at site to hoisting

Key Construction Wastes in Precast Construction

2

3

4

5

6

7

8

9

10

11













Focus on Create Use Level Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment Out the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers

1

Table 4.3 (continued) 12

13

14



(continued)



Observe Consider Review and Alternative Process Understand Solutions the Process √

4.6 Gaps in Current Research 73

Overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

Key Construction Wastes in Precast Construction

2

3

4

5

6

7

8

9

10

11

Focus on Create Use Level Stop to Standardise Visualise Adapt to Empower Develop Grow Together Long-Term One-Piece Pull-Replenishment Out the Fix Tasks Process Operations your your with Solid Results Flow Workload Problems People People Subcontractors and Suppliers √

1

Table 4.3 (continued) 12

13

14

Observe Consider Review and Alternative Process Understand Solutions the Process

74 4 Lean Construction Implementation

Chapter 5

Shared Mental Models Development

5.1 Overview In this chapter, it is proposed that the shared mental models theory provides a theoretical foundation to explain the importance of lean construction implementation for total manpower reduction in precast construction. This is because the literature on lean construction and the literature on shared mental models theory have an overlapping interest in improving team performance which corresponds to the main emphasis of this research on reducing manpower effort in precast construction by eliminating construction wastes that does not deliver value. Through this application, this research anchors the conceptual model development to underpin the tenets of enabling lean in precast construction, rather than a discussion of how shared mental models theory applies to each lean principle. Hence, this chapter is organised as follows. First, the theory of shared mental models and its relevance to this research will be explained. Next, the value of enabling lean in precast construction in the context of shared mental theory will be illustrated. Lastly, the conceptual model will be developed to help contractors identify the areas which can be improved, potential total man-day savings to be gained and the plausible, incremental steps for improvement.

5.2 Shared Mental Models Theory Shared mental models is a theory from cognitive psychology which has a strong position in investigating the role of shared understanding on team performance with a focus on the thought processes or activities that occur at a team level. The shared mental models theory is an extension from the mental model theory which reasons that an individual’s mind holds representations of anything that an individual has

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_5

75

76

5 Shared Mental Models Development

encountered when learning new knowledge or solving problems (Johnson-Laird 1983). Converse et al. (1993, p. 221) defined shared mental models as the: knowledge structures held by members of a team that enable them to form accurate explanations and expectations for the task, and, in turn, to coordinate their actions and adapt their behaviour to demands of the task and other team members.

The conception of the shared mental models established from several studies (see Table 5.1) is illustrated in Fig. 5.1. According to Converse et al. (1991), team members working together have to possess shared mental models and the closer the development of their shared mental models, the better they can collaborate with each other to result in successful outcomes. Shared mental models can provide all the manpower involved throughout the precast construction process with an internal knowledge base that allows them to decide what actions to take. Through shared mental models, the team members involved throughout the precast construction process will develop a common understanding of the (i) nature of the task; and (ii) the way the team should work together so that manpower reduction is possible. Taskwork mental model is about the tasks to be performed such as recognising the goals, complexities and procedures to accomplish the tasks. Teamwork mental model is about how the team will interact such as communication patterns, roles and responsibilities of team members and role interdependencies. Detailed knowledge of a teammate’s task allows a team member to determine the types of information and assistance that a teammate needs. Further, detailed knowledge of the demands imposed by various environments provides realistic expectations about when the demands of tasks are likely to vary, and which teammates are likely to be overloaded. Accurate and detailed knowledge of the relationships that exist between individual tasks and the quality of overall team performance allows team members to assign realistic priorities to the performance of specific tasks. Team members involved should share closeness in their taskwork and teamwork mental models as both are significantly positively related to reduce construction wastes throughout the precast construction process which are in turn significant to enhance team performance (Mathieu et al. 2000). This is because team members may share a common vision but are mistaken about the circumstances that they are facing. Although team members are working together cohesively, they may be working on something ancillary, lowering the overall level of team performance (Andres 2012). This will cause a higher occurrence of construction wastes which translates to higher manpower effort required throughout the precast construction process. Moreover, the extent of correctness of the taskwork mental model will influence the team members’ understanding of the tasks and have an impact on the team performance (Lim and Klein 2006). Likewise, if their teamwork mental model is incorrect, team members will encounter unnecessary disagreement and work inefficiently and ineffectively (Hsu et al. 2011). This is because team members may be working in the wrong direction which will trigger more frequent occurrence of construction wastes and more effort is required to turn the situation around throughout the precast construction process. Team members may also not have the correct frame of mind which will

5.2 Shared Mental Models Theory

77

Table 5.1 Proposed characteristics of shared mental models theory for precast construction Sources

Andres Canonne (2012) and Aucouturier (2016)

Taskwork Mental Models √ Team members reconcile conflicts and reconfirm goals Team members develop introspective practices Team members share information that is previously possessed individually by each team member to others in the team Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them



Team members integrate information and determine the consequence Teamwork mental models Team members have a common goal and form compatible expectations to act accordingly

Cassidy Dionne Evans and et al. and Stanley (2010) Ross (2018) Baker (2012)

Maynard and Gilson (2014)



Van den Bossche et al. (2011)

Schmidtke and Cummings (2017)





































(continued)

78

5 Shared Mental Models Development

Table 5.1 (continued) Sources

Team members collaborate and work closely through a structured means of communication

Andres Canonne (2012) and Aucouturier (2016) √

Team members get another’s information requirement accurately and quickly

Maynard and Gilson (2014)

Van den Bossche et al. (2011)



Schmidtke and Cummings (2017) √



Team members are committed and motivated to meet the client’s needs Cross-training to equip team members with a shared knowledge of their teammates’ work

Cassidy Dionne Evans and et al. and Stanley (2010) Ross (2018) Baker (2012) √













Note The list highlighted the main points from the more pertinent sources to reduce construction wastes and manpower effort in precast construction. This will be used in the Survey Questionnaire as elaborated in Chapter Six

cause difficulties in the minimisation of construction wastes and more manpower effort is required to deal with conflicts that may arise to carry on with the precast construction process. As shared understanding increased, behaviours will be more cooperative and ideas proposed will become more complementary to the requirements. A shared interpretation of the requirements and solutions will promote efficiency by minimising processing of irrelevant information so that it is easier to arrive at a consensus (Canonne and Aucouturier 2016). Therefore, having shared mental models is important in relating lean in precast construction to result in lower utilisation of manpower effort (Dao et al. 2017).

5.3 Underpinning Lean Construction Implementation in Precast Construction

79

Fig. 5.1 Conception of shared mental models

5.3 Underpinning Lean Construction Implementation in Precast Construction 5.3.1 Design Stage From the lens of shared mental models theory during the design stage of precast construction, the role of taskwork and teamwork mental models is critical to prevent construction wastes downstream as the design stage is where the most project value can be gained or lost and there is substantial room for improvement to reduce the overall manpower effort. The building design should be based on team members’ understanding of the project value and minimising the elements that contribute to construction wastes. The necessary value-added requirements are to be delivered considering the life-cycle perspective and hence contractors should be brought in from the design phase to ensure that constructability issues are considered to optimise the allocation of manpower. Value engineering should also be institutionalised into the design process with a greater focus on constructability. The contractor may know of a way to do certain tasks at the same time to reduce construction duration, rather than sequentially and able to suggest new ways to minimise the manpower required.

80

5 Shared Mental Models Development

During the design stage of precast construction, team members can build up an all-encompassing insight to enhance the shared understanding of the task and the team (Cassidy and Stanley 2018). This will encourage team members to share information that is previously possessed individually by each team member to be able to figure out the overall picture of the project (Schmidtke and Cummings 2017). Team members can also discuss on how to react to unexpected events, identify significant risks and prioritise actions to address them (Stout et al. 1999; Dionne et al. 2010). They will standardise and resolve the tasks immediately so that the problems will not be duplicated in the next cycle. The thinking process are to be done without preconceptions and with a blank mind and this will also enable them to grow and become better team members to deliver the precast construction project. By enabling each team member to not only have a clear understanding and commonality of the task goals and the steps needed to accomplish the goals, the precast construction process can be sustained (Marks et al. 2000; Evans and Ross 2012). Hence, it is evident that the lean principles can improve the taskwork and teamwork mental models throughout the precast construction process.

5.3.2 Production Stage Lean principles also aid in the creation of a shared mental models within the team of stakeholders during the production stage of precast construction. There are opportunities to increase the team’s shared understandings about the taskwork through daily monitoring and control of the project’s progress. This is so that team members form compatible expectations to act accordingly (Smith-Jentsch et al. 2008). Team members will have shared knowledge of the option and therefore focus on those that have higher opportunities of success (Lim and Klein 2006). Further, the application of lean provides a chance for team members to learn more about each other progress, roles and skills. Cross-training is to be conducted to equip team members with a shared knowledge of their teammates’ work (Volpe et al. 1996). This can help them to gain greater teamwork mental model and compensate for their teammates’ limitations. With that, they will be able to better adapt to changing circumstances and collaborate with other team members smoothly. Production tasks may be challenging and unachievable at the first glance as they are more familiar with the traditional construction approach. If the necessity of utilising technology and precast construction is convincingly explained to all team members and driven by the top management, they will become enthusiastic in the spirit of challenge and will work together and achieve it. Lean construction implementation encourages team members to freely and openly share their opinions to reflect on their performance to date, to identify how to implement improvements as well as implement the new improvements (Salas and Foire 2004). Through these interactions, team members develop shared understandings of the consequences of the current approach and future steps. Should the consequences be manifested, the team is more

5.3 Underpinning Lean Construction Implementation in Precast Construction

81

likely to be able to respond quickly to the situation. This can stimulate suggestions on how to streamline the production process to reduce the manpower requirements.

5.3.3 Logistics Stage Using the shared mental models theory as a lens, applying lean principles are important to avoid failing courses of action during the protection, transportation and lifting processes. There is a need to encourage stronger levels of commitment and enhance the team’s motivation to enforce them to make sure that precast construction process is duly followed through even after the precast components leave the factory and before the final installation is completed (McComb 2007). Team members should plan to cut down on the time and motion when delivering the precast components to site prior to lifting by upholding the JIT approach (Goh and Goh 2019). Team members are to integrate information from each other to determine the resources required for the tasks to result in efficient and effective logistics management throughout the precast construction process (Espevik et al. 2011). Team members are to develop understanding and learn about the different tasks involved in precast construction to improve their executing capability (Van den Bossche et al. 2011). Hence, lean principles will be effective in creating taskwork and teamwork mental models among team members, which in turn enhance the reduction of construction wastes and manpower utilisation.

5.3.4 Installation Stage After the installation of each precast component, team members should gain more knowledge and are able to install the next component better through constant improvement. This is to be practiced in a very consistent manner in a concrete way by all team members. There should be a systematic approach to create a shared and correct understanding of one another’s roles, responsibilities, and technical backgrounds as well as develop a pattern of team communication and coordination (Yu and Petter 2014). This will enable more correct anticipations of their team members’ informational requirements which is promptly obtained to prevent any extra-processing (Zhang 2012). This is especially relevant and important because of the presence of many stakeholders that have differing technical specialities and are responsible for different scope in the precast construction process. Using BIM to implement VDC, each team member gains awareness of one another’s scope and can identify previously unshared information by coordinating using a common language (Warner et al. 2005; Maynard and Gilson 2014). This process is necessary to significantly reduce construction wastes and streamline the allocation of manpower. Finally, the review process is critical for team members to develop introspective practices to better adapt and address changing circumstances

82

5 Shared Mental Models Development

(Gurtner et al. 2007). This will ensure that the important aspects relevant to the precast construction tasks and the team are discussed to see if it is possible to further minimise construction wastes and the manpower effort required.

5.4 Summary Following through the literature review done in Chapter Three and Chapter Four on the construction wastes and lean principles to be applied during the respective precast construction stages, this chapter explains how team members need to develop shared mental models in enabling lean during precast construction to result in optimal usage of manpower. The shared mental models theory is applied to study the teamwork and taskwork of the precast construction process and to assess how the fourteen lean principles can bring about reduction of construction wastes and influence the total man-days to be utilised. To recap, team members in this study refer to site management members from the main contractors as well as management members from the precasters as depicted in Fig. 1.1. This team needs to work together to direct the labourers to perform their tasks in the most efficient and effective manner in the precast construction process. Team members working together have to possess shared mental models and the closer the development of their shared mental models, the better they can collaborate with each other to result in successful outcomes. During the design stage, it can be seen from the perspective of shared mental models that team members have to share information to facilitate the creation of one-piece flow, develop best practices to enhance the shared understanding of the task and the team, and discuss how to react to unexpected events, identify significant risks and prioritise actions to address them together with their subcontractors and suppliers. During the production stage, precasters need to manage the quality of the precast components, having skilled workers and proper supervision in the factory to perform and monitor the works so as to prevent defects and reworks. Next, through daily monitoring and alignment, team members can form compatible expectations as they plan their production and installation schedule to facilitate the pull system to minimise inventory. Also, cross-training is required to equip team members with a shared knowledge of their teammates’ work so that they become competent to look out for areas which have gone wrong before continuing with the next activity. During the logistics stage, there is a need to encourage stronger levels of commitment to enforce team members to follow through and sustain the effort that has been ensured in the earlier stages. This is to inculcate a culture of stopping to fix problems. To do so, team members are to integrate information from each other to determine the resources required for the tasks to result in efficient and effective logistics management. During the installation stage, team members should gain more knowledge with the repeated installation of precast components. They should be able to guide the workers to install the next component better in a systematic approach to create a

5.4 Summary

83

shared and correct understanding of one another’s roles, responsibilities, and develop a pattern of team communication and coordination. The review process should also be conducted for team members to develop introspective practices to better adapt and address changing circumstances.

5.5 Proposed Conceptual Model Precast construction is rapidly adopted as contractors search for methods to remove the wastes to result in manpower savings both on-site and off-site. Studies examining lean construction showed that it can be implemented in precast construction which is also reinforced by the shared mental models theory. Table 5.2 explains how lean construction creates taskwork and teamwork mental models in precast construction to result in optimal usage of manpower. Precast construction productivity performance is better when team members work together from end-to-end in a lean manner as diagrammed in Fig. 5.2. This blending of two seemingly different disciplines – Shared Mental Models and Lean Principles strengthens the outcome as team members participate in interdependence throughout every stage of the precast construction process. In each precast construction project, the design should be settled upfront while the production, logistics and installation stages are iterative. Overall, contractors need to strengthen their fundamentals and build up their enterprise precast construction capability to sustain the implementation of precast construction in Singapore. The proposed conceptual model developed in Fig. 5.3 showcases how the application of lean principles for precast construction is impacted by the characteristics of shared mental models theory to result in the reduction of construction wastes and manpower changes. This means that the characteristics of the shared mental models theory will intervene with the effect of lean construction implementation on the construction wastes to be removed and manpower changes. As such, the five hypotheses stated in Chapter One are proposed. All in all, the team members involved in the precast construction should be aligned towards a common purpose to achieve lean construction by moving away from the traditional sequential approach and involve relevant stakeholders early at the design development stage to give inputs on downstream construction issues. This will ensure that the different players can contribute and have an in-depth understanding of the work to streamline the manpower effort. Team members must develop a shared culture that can support them to do the work, garner them to challenge the proposed ideas and come up with substantive solutions, one that has been considered thoroughly and not just a concept idea without any upfront planning and due diligence done. The proposed conceptual model will be tested and validated in the subsequent primary research.

Defects and rework due to improper interfacing between precast components resulting in extra-processing (CW3)

Interfacing Coordination and Connection; Alignment and Construction Tolerance

Factory location and capacity; plant and machinery capabilities

Overproduction due to poor control of precast quantities resulting in the need for inventory (CW4)

Extra-processing due to design changes (CW2)

Standardisation, simplification and single integrated elements; design approvals

Production

Defects and rework due to incompatibility of design with downstream precast construction processes (CW1)

Key construction wastes to be removed (chapter three)

Early contractor involvement; accessibility for assembly

Design

Key precast construction considerations (chapter three) Create one-piece flow (LP2) Visualise process (LP7) Adapt to operations (LP8) Grow together with solid subcontractors and suppliers (LP11)

• Use pull-replenishment (LP3) • Level out the workload (LP4) • Consider alternative solutions (LP13)

• Stop to fix problems (LP5) • Visualise process (LP7) • Observe and understand the process (LP12)

• Focus on long-term results (LP1) • Create one-piece flow (LP2) • Standardise tasks (LP6)

• • • •

Key lean principles (chapter four)

Table 5.2 Analysis of enabling lean in precast construction using the lens of shared mental models theory

• Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them. (SMM4) • Team members have a common goal and form compatible expectations to act accordingly. (SMM6) (continued)

• Team members share information that is previously possessed individually by each team member to others in the team. (SMM3) • Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them. (SMM4) • Team members have a common goal and form compatible expectations to act accordingly. (SMM6) • Team members collaborate and work closely through a structured means of communication. (SMM7)

Key shared mental models characteristics (chapter five)

84 5 Shared Mental Models Development

Motion from the arrival of the precast • Use pull-replenishment (LP3) components at site to hoisting (CW8) • Consider alternative solutions (LP13)

Lifting

• Stop to fix problems (LP5) • Visualise process (LP7)

Waiting and idle time and transportation for the delivery of precast components across multiple sites (CW7)

Protection; transportation

Logistics

Non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework (CW6)

Human resource management

• Focus on long-term results (LP1) • Empower your people (LP9) • Develop your people (LP10)

Waiting and idle time due to the need • Stop to fix problems (LP5) to conduct a thorough quality control • Observe and understand the and assurance procedure in precast process (LP12) construction which contributes to inventory (CW5)

Total quality management

Key lean principles (chapter four)

Key construction wastes to be removed (chapter three)

Key precast construction considerations (chapter three)

Table 5.2 (continued)

• Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them. (SMM4) • Team members get another’s information requirement accurately and quickly. (SMM10) (continued)

• Team members integrate information and determine the consequences. (SMM5) • Team members are committed and motivated to meet the client’s needs. (SMM8)

• Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them. (SMM4) • Cross-training to equip team members with a shared knowledge of their teammates’ work. (SMM9)

Key shared mental models characteristics (chapter five)

5.5 Proposed Conceptual Model 85

• Visualise process (LP7) • Consider alternative solutions (LP13)

• Team members share information that is previously possessed individually by each team member to others in the team. (SMM3) • Team members get another’s information requirement accurately and quickly. (SMM10)

• Team members develop introspective practices. (SMM2) • Team members share information that is previously possessed individually by each team member to others in the team. (SMM3) • Team members collaborate and work closely through a structured means of communication. (SMM7)

• Team members reconcile conflicts and reconfirm goals. (SMM1) • Team members collaborate and work closely through a structured means of communication. (SMM7)

Key shared mental models characteristics (chapter five)

Note The list highlighted the key points to analyse lean in precast construction using the lens of shared mental models theory. This will be used in the Survey Questionnaire as elaborated in Chapter Six

Overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing (CW11)

Info-communications technology

Focus on long-term results (LP1) Stop to fix problems (LP5) Adapt to operations (LP8) Grow together with solid subcontractors and suppliers (LP11) • Consider alternative solutions (LP13)

• • • •

Key lean principles (chapter four)

• Stop to fix problems (LP5) • Visualise process (LP7) • Review process (LP14)

Non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction (CW9)

Key construction wastes to be removed (chapter three)

Building information modelling and Defects and rework due to virtual design and construction; non-compliance to quality critical inspections and quality checks requirements of precast construction (CW10)

Construction and project management

Installation

Key precast construction considerations (chapter three)

Table 5.2 (continued)

86 5 Shared Mental Models Development

Fig. 5.2 Working together from end-to-end in a lean manner for precast construction capability development

5.5 Proposed Conceptual Model 87

5 Shared Mental Models Development

Fig. 5.3 Proposed conceptual model

88

Chapter 6

Research Design and Methodology

6.1 Research Design The objectives of this research were discussed in Chapter One. In Chapter Two, literature of the Singapore’s construction industry in terms of productivity advancement was reviewed to provide an understanding of the issues, effectiveness of measures taken and outlook of productivity growth in the years to come. In Chapter Three and Four, an extensive literature review of how precast construction and lean construction came about, factors that causes construction wastes in precast construction and the implementation of lean to streamline the total manpower requirements were discussed. The conceptual model was then set up in Chapter Five. In this chapter, details of the primary research design and data collection method are discussed. The research process was designed in accordance with the research objectives to further understand the occurrence of construction wastes throughout the precast construction process and evaluate lean actions that should be taken to reduce the total man-day requirements. Using the data collected from the surveys, a series of descriptive and inferential statistics and neural network were utilised to test and train the proposed conceptual model to predict the classification of precast projects under high risk or low risk of poor construction productivity. Interviews were done to validate the survey results and a case study was conducted to validate the neural network model generated. Lastly, a conclusion of the research is presented, with suggestions for further studies. Figure 6.1 is constructed to demonstrate the overall research design.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_6

89

90

6 Research Design and Methodology

Fig. 6.1 Overall research design

6.2 Data Collection Method Questionnaire survey was conducted to find out the relationships among the various components in the proposed conceptual model. The population sampled consists of key team members from precast construction projects who manages the workers and would be in a direct position to impact the lean construction considerations through shared mental models development throughout the precast construction process. They are from the main contractor’s site management team and precaster who is the subcontractor responsible for the precast concrete works which is the scope of this research. Each of the five team members were required to respond based on their respective roles in the project as they play an important role in influencing the occurrence of constructions wastes and manpower efforts deployed. To ensure the currency of the population to be sampled, 186 unique general building contractors were shortlisted from BCA (2019c)’s Construction Project Database based on the criteria stated in Table 6.1. This is due to the frequent changes in the buildability and productivity regulations which have been made to be more stringent over the years to encourage the industry to move away from labour intensive construction methods. The following criteria will also ensure that the respondents

6.2 Data Collection Method

91

Table 6.1 Criteria for population to be sampled Criteria

Population

No. of contracts

≥1

Date of award/work commencement

After 1 January 2015

Date of completion

By 30 June 2019

GFA

≥5,000m2 (monthly construction productivity data are to be submitted to BCA for projects with GFA of 5,000m2 or more)

Contract cost

≥S$10 M (Assumption: 5,000m2 x S$1,700/m2 × 20% external works and miscellaneous cost)

have relevant knowledge and experience in tracking their construction productivity level and managing different types of building development projects of substantial size to adopt precast construction. The sample selection was carried out by purposive sampling to ensure that the respondents are directly involved in the project, hence able to provide useful responses. Survey questionnaires were sent via post and email to the director of each company who was asked to nominate five key roles who have been involved in precast construction projects to respond individually. Responses were also solicited through engagements made in a built conference event. Since they were nominated, a certain level of reduction in social desirability and personal bias was achieved. The preliminary questionnaire shown in Appendix B was piloted together with two main contractors. Through the pilot survey, it was found that they are continuously improving their construction management practices as well as trying to improve their productivity performance through various methods. As the survey questionnaire was constructed based on the literature review as well as consultation sessions conducted with the industry practitioners, a neutral view is essential. In the selection of this neutral view, their knowledge of the current precast construction market have been ascertained by checking their alignment with the review done in Chapter Three. This is so that their feedbacks and comments to the structure of the questions can be gathered and any issues and problems with the questionnaire can be identified. This is to enhance the accuracy of the survey, having questions that are correctly designed to serve their intended purposes. Based on inputs obtained from the pilot survey as well as materials gathered from the literature review, a final questionnaire was then formulated for a full-scale survey to be conducted as shown in Appendix C. The main improvements from the pilot questionnaire to the final questionnaire are that more information on the objective of the survey and some background about lean construction were make known to the respondents. Further, the pilot questionnaire found that the definition of the 7-point Likert scale used were not intuitive for them to rate the changes in the occurrence of construction wastes and manpower used. Hence, the final questionnaire structured the answers on the changes in terms of a range of percentages as shown in Table

92

6 Research Design and Methodology

Table 6.2 Transforming Likert scale to range of percentages Rating

Definition

Occurrence of construction wastes

Manpower changes

1

Moderate increase

>20–40% more wastes

>10–20% more man-day

2

Slight increase

0–20% more wastes

0–10% more man-day

3

About the same

No change

No change

4

Slight reduction

0–20% less wastes

0–10% less man-day

5

Moderate reduction

>20–40% less wastes

>10–20% less man-day

6

Major reduction

>40–60% less wastes

>20–30% less man-day

7

Extreme reduction

>60–80% less wastes

>30–40% less man-day

6.2 which was formulated in discussion with the two main contractors in the pilot survey. Respondents were asked to report the percentage changes based on their experience with no means to verify the figures as it is impossible to track and account for the changes in the occurrence of construction wastes and man-day utilised as a result of the situations given. Hence, there could be a problem of common method variance. Further, the respondents may have the urge to maintain a consistent line in a series of answers. To minimise such problem, the scale-reordering method in which measures of independent variables (occurrence of construction wastes) were asked before dependent variables (manpower changes) in the questionnaire. For the first question in the survey, general information about the respondents were collected mainly to understand how experience in the industry affected their responses and the way they manage precast construction projects. For the second and third question in the survey, respondents were required to fill in the productivity monitoring data of all their projects adopting precast construction with GFA greater than 5,000m2 and completed after Year 2015. This data would be used for the subsequent validation process which would be elaborated in Sect. 6.4. For the fourth question in the survey, each of the five key members who are responsible for the following roles or equivalent, namely Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and a representative from their precaster, were asked to assess the expected changes from −80% to + 40% the occurrence of construction wastes during the precast construction process because of shared mental models and lean principles implementation. This is to understand the impact on the occurrence of construction wastes based on the way team members work together and with the influence of lean construction implementation. Lastly, for the fifth question in the survey, each of the five key members were questioned on the expected changes from −40% to + 20% in the total manpower used during the precast construction process resulting from minimisation of the construction wastes. This is to understand the impact on the total man-day used when efforts are made to reduce the construction wastes. The question was asked in terms of man-day so that respondents do not interpreted the question as number of

6.2 Data Collection Method

93

workers which does not give a true representation of the total manpower used. The outcome would be used for the subsequent prediction model to classify the risk of low construction productivity.

6.3 Data Analysis Method 6.3.1 Overview The IBM SPSS (Statistical Package for Social Science) Statistics and IBM SPSS Modeler were used to analyse the data collected. Descriptive statistics such as the means, percentages and standard deviations were computed to form the basis for subsequent quantitative data analysis and allow for greater understanding of the data trends. This ensures the credibility of the responses and identify if there are significant factors that may indicate a non-representative sampling of the target population. Cronbach’s alpha was calculated to ascertain the consistency of respondents’ responses to the attributes measuring the same construct for question four and five of the survey. None of the attributes’ Cronbach’s alpha improves significantly after its deletion and hence, no attributes were removed. The questionnaire was deemed to be reliable, demonstrating convergent validity. The central limit theorem states that sample means will be approximately normally distributed if there are at least 30 random samples from the population, regardless of whether the population is normal or skewed. As the number of responses obtained is 115, the distribution is deemed to be normal. As responses were obtained from team members undertaking five different roles in a precast construction project, the Kruskal–Wallis test was done to examine and compare the mean rank of these five groups. Kruskal–Wallis test was selected as these five groups of data are independent and the scale of the variables is ordinal. Moreover, Kruskal–Wallis test does not make assumptions about normality which is suitable in this study as the dataset in three out of the five groups are less than 30.

6.3.2 Hypotheses Testing Next, the fourteen attributes under the lean principles (Factor 1), ten attributes under the shared mental models (Factor 2) and eleven attributes under the manpower changes (Factor 3) were respectively combined. Given that the scale of these 35 attributes is order, the median value (rounded up to the nearest rating) is computed for further analysis. Spearman rank-order correlation coefficient tests were then conducted to determine the relationships between these three factors and address Hypotheses 1–5. The Pearson correlation was not chosen as it can only be used for

94

6 Research Design and Methodology

interval or ratio scale but this study is using ordinal scale. However, the correlation analyses cannot verify the causative effect. Although correlation is a powerful method to describe and test associations, it is not able to predict the value of one dependent variable, from measurements of the other independent variables. Following that, the leading indicator of precast productivity performance was constructed by categorising the 115 responses into two class—“Below Threshold” and “Above Threshold”. “Below Threshold” means that contractors are deemed to be at a high risk of low precast productivity performance. “Above Threshold” means that contractors are deemed to be at a low risk of low precast productivity performance. Given that the mean rating is approximately 5 for each of the three broad factors (LP1 to LP14, SMM1 to SMM10 and CW1 to CW11), responses with a rating of 5 and above for all three factors will be categorised under “Above Threshold” while the rest of the responses will be categorised under “Below Threshold”. With that, the prediction model was developed to classify how the changes in the occurrence of construction wastes affects the precast construction productivity performance.

6.3.3 Neural Network As there is a clear set of parametric inputs and target variables, supervised learning is the preferred method for the prediction of the effects of the occurrence of constructions wastes due to lean construction implementation and shared mental models development on the leading indicator of precast productivity performance. There is no hierarchical relationship in the inputs and hence, the decision tree related algorithms such as Random Forest and Classification and Regression Tree are not suitable for this study. Logistic regression is also not suitable as it is unable to provide an understanding of the non-linear relationship of the data. The method chosen does not assume the linearity and learn directly from the data to predict the outcome, which is essentially the leading indicator, a proxy to the risk of low construction productivity that the project poses. Areas for further improvement would be determined to result in greater reduction in manpower and boost construction productivity without compromising on other aspects such as quality and safety. As depicted in the proposed conceptual model, the inputs are inter-related and work together which resembles the neural network approach, operating like neurons in the human brain. The neurons in the neural network are connected by links and, these neurons contain functions and are connected to other neurons. Hence, the neural network method, which allows algorithms to be run without any user-imposed conditions, is chosen for this study. In the neural network, each learning cycle involves a forward pass where an example is presented as an input to the network (Chang 2005). The predicted outputs from the neural network were compared with the expected output obtained from the respondents. The error, as defined by the difference between predicted output and expected output, facilitates a backward pass through the network to adjust the weights of the connections between neurons to minimise the error (Samarasinghe 2016).

6.3 Data Analysis Method

95

The criteria for the network that provided the best fit was one which produced the lowest cross entropy value which is meant for classification problem. Cross entropy will calculate a score that summarises the average difference between the actual and predicted probability distributions for predicting the respective two classes—“Above Threshold” and “Below Threshold”. According to Loukas (2000), the ratio of the number of predictor variables applied and data points gathered is recommended to be around 0.1 to avoid overfitting for studies using neural network for prediction. Wang and Buchanan (2002) stated that this ratio could be around 0.2 for noise-free data and achieving a ratio of around 0.03 would be the best way to avoid overfitting. In the study by Cheung et al. (2000), the neural network generated for classifying the outcome of project dispute resolution as “Favourable” or “Adverse” gave a ratio of 0.23 (14 predictor variables and 61 data points). In this study, there are 24 predictor variables and 115 observations and the ratio is 0.21. The number of predictor variables was not reduced to achieve a lower ratio like what Rebano-Edwards (2007) have done because the descriptive statistics and reliability tests conducted for these 24 predictor variables did not result in the need to eliminate any variables. Hence, the number of data points vis-à-vis the number of variables used is deemed to be workable to generate the neural network model. The training sets were presented to the network until the output error is minimised or below a specified acceptable limit to generate a model without overfitting. Hence, a mathematical functional relationship between the input and output data does not need to be specified unlike multiple linear regression (Williams et al. 2009). The neural network weights and biases were assigned using the generated random numbers. The network learns and adjusts the weight assigned to the links to improve its performance. The optimal number of neurons was determined based on a random approach to allow for a high quality, smooth fit of the line through the known points (Efron 1983; Kim 2017). This is because if there are too few neurons, the neural network will not converge well. Williams et al. (2009) noted that too many neurons will result in the neural network over-fitting the line, which leads to inaccurate prediction of the manpower changes corresponding to the lean principles. Further, one hidden layer was selected as recommended by Schalkoff (1997) and Kim and Gilley (2008) as this can achieve high accuracy and that it is rare to have more than two hidden layers. The fundamental idea of the proposed prediction model is to anticipate, recognise, evaluate, resolve, control and learn from past experiences. Unlike regression methods, the neural network model provides dynamic output as further data is fed to it but it cannot tell the correlation and which inputs are more important (Rao et al. 2010). Hence, the prediction using neural network is more reliable than the regression method. Consequently, the contractors can improve and apply these experiences in their precast construction projects, implementing lean construction for reducing construction wastes to streamline the total man-days.

96

6 Research Design and Methodology

Table 6.3 Number of post-survey interviews gathered from recent Doctoral’s theses S/N

Citation

1

Leni, S. R. S. (2014). Implementing Business Continuity Management 5 (BCM) using a Knowledge Based Decision Support System (KBDSS) for Indonesian contractors (Doctoral’s thesis). National University of Singapore, Singapore

No. of Interviews

2

Zhao, X. B. (2014). Enterprise risk management in Chinese construction firms operating overseas (Doctoral’s thesis). National University of Singapore, Singapore

4

3

Kazuhito, S. (2017). The impact of national culture on communication management—Japanese contractors in Singapore construction industry (Doctoral’s thesis). National University of Singapore, Singapore

6

4

Liao, L. H. (2018). Building Information Modelling-based process transformation to improve productivity in the Singapore construction industry (Doctoral’s thesis). National University of Singapore, Singapore

5

6.4 Validation According to other recent Doctoral’s theses completed in the NUS Department of Building which have used interviews to validate the survey findings, the total number of post-survey interviews conducted were between four to six as shown in Table 6.3. Hence, a total of six post-survey interviews (three main contractors and three precasters) were selected to validate survey results. Main contractor was chosen as she is the party responsible for managing the precast construction process—design, production, logistics and installation. Moreover, four (Project Manager, Site Structural Engineer, Architectural Coordinator and M&E Coordinator) out of five of the key team members in this study are from the main contractor. During the design stage, the main contractor would have to advise the consultants on how to standardise the design and provide constructability inputs to ensure that manpower usage during the downstream production, logistics and installation stages could be streamlined with the removal of construction wastes. Precaster was also chosen, being the fifth key team member of interest in this study. A precaster is involved to manage the production and logistics stages of the precast construction process based on the main contractor’s request. With inputs from the main contractor, the precaster would then work on how to optimise the number of moulds used, the space planning within the factory and delivery of the precast components to site in accordance with the given schedule. Nevertheless, the main contractor’s involvement to ensure the quality of the precast components during the production and logistics stages is also critical to prevent reworks. Lastly, during the installation stage, the main contractor would have to plan the installation schedule taking into consideration the site constraints such that the precast component could

6.4 Validation

97

Table 6.4 Details of interviewees S/N

Interviewee

Designation

Years in Construction Industry

Company’s Area of Expertise

Verbatim

1

Mr A

Senior Operations Manager

28

Precaster

Appendix E

2

Mr B

General Manager

34

Main Contractor

Appendix F

3

Mr C

Assistant General Manager

32

Precaster

Appendix G

4

Mr D

Technical Manager 11

Main Contractor

Appendix H

5

Mr E

Senior Project Manager

13

Main Contractor

Appendix I

6

Mr F

Chief Operating Officer

24

Precaster

Appendix J

be installed once it is being delivered to site, eliminating the need for waiting time and inventory. These six interviews serve to enhance the validity of the quantitative results with the conduct of qualitative research by probing specific open-ended questions that the survey questionnaire is unable to address. The guiding questions used are shown in Appendix D. The verbatim of the interviewees, as listed in Table 6.4, are captured in Appendix E to J. The conduct of these in-depth interviews was done in a face-to-face manner at the interviewee’s office to encourage them to give their responses honestly and freely to ensure reliable qualitative data. The interview questions may vary among the interviewees, depending on their company, individual profile, and their involvement in the project. The questions were asked to validate the observations obtained from the survey results to ensure that the survey and prediction model is of sufficient rigor with multiple sources of evidence to back up claims with explanation. Lastly, two projects obtained from the survey were used to validate against the neural network generated by evaluating their project’s productivity data and assessing the attributes to reduce construction wastes and manpower used. Their predicted leading indicator of productivity performance and actual productivity figure was also compared. The outcome generated was used to draw conclusions on what lean construction considerations and shared mental model attributes were lacking such that the construction wastes still occur and what the project could have done to further optimise the utilisation of manpower.

Chapter 7

Results and Analysis

7.1 Overview of Research Analysis The purpose and overall structure of the research analysis to give an overview of the steps taken in this research to analyse the findings obtained is shown in Table 7.1 and Fig. 7.1.

7.2 Analysis of Respondents The questionnaire survey was conducted over two months around July 2019 to August 2019. Out of the population size of 186 as explained in Chap. 6, a total of 32 companies responded. Of these 32 companies, the response rate of each of the five team members is shown in Fig. 7.2. Hence, the total valid responses at 115 (or 72%) is considerably high and deemed to not contain significant non-response bias and is reliable (Baruch and Holtom 2008; Anseel et al. 2010). 69% of the respondents are from a general building contractor with unlimited tendering limit as shown in Fig. 7.3. The years of experience in the construction industry of each team member who responded ranged from 2 to 40 and the average years of experience of each team member is shown in Fig. 7.4. Therefore, the varying level of experience and their involvement in their respective roles throughout the precast construction process are adequate to ensure the quality and accuracy of the data to yield representative results.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_7

99

100

7 Results and Analysis

Table 7.1 Purpose of research analysis Type

Purpose of analysis

Descriptive statistics (survey)

Mean Rating—To verify the percentage range of the reduction in the occurrence of construction wastes as well as the extent of changes in the total man-days used based on the results obtained

Inferential statistics (survey)

Hypothesis 1—To determine the strength of dependence between the reduction of construction wastes due to the implementation of lean construction principles and the reduction of construction wastes due to the development of shared mental models, through the Spearman rank-order correlation coefficient test Hypothesis 2—To determine the strength of dependence between the reduction of construction wastes due to the implementation of lean construction principles and the extent of changes in the total man-days used, through the Spearman rank-order correlation coefficient test Hypothesis 3—To determine the strength of dependence between the reduction of construction wastes due to the development of shared mental models and the extent of changes in the total man-days used, through the Spearman rank-order correlation coefficient test Hypothesis 4—To determine if there is a relationship between the reduction of construction wastes due to the implementation of lean construction principles and the leading indicator of precast productivity performance, through the Spearman rank-order correlation coefficient test Hypothesis 5—To determine if there is a relationship between the reduction of construction wastes due to the development of shared mental models and the leading indicator of precast productivity performance, through the Spearman rank-order correlation coefficient test

Neural network model

To determine the predicted leading indicator of precast productivity performance based on the different extent of reduction of construction wastes due to the adoption of the lean construction principles with the development of shared mental models

Validation of survey results (interviews)

In the process of explaining the results of the descriptive and inferential statistics, findings from the six interviews conducted were used to validate the survey data analysis

Validation of neutral Two precast construction projects were used to validate the neural network model (case study) network model generated from the survey responses

7.2 Analysis of Respondents

101

Fig. 7.1 Overall structure of research analysis process 35

32

32

30 25 20

Project Manager 18

17

15 10 5 0

Fig. 7.2 Response rate of each team member

Site Structural Engineer 16

Architectural Coordinator M&E Coordinator Precaster PIC

102

7 Results and Analysis

B1 (up to S$40M) 9%

B2 (up to S$13M) 13%

A2 (up to S$85M) 9%

A1 (unlimited) 69%

Fig. 7.3 Respondent breakdown by company’s tendering limit

25

20

15

20

15

Project Manager Site Structural Engineer

13 11

11

10

Architectural Coordinator M&E Coordinator Precaster's Representative

5

0 Fig. 7.4 Average years of experience of each team member

7.3 Analysis of Variance

103

7.3 Analysis of Variance To assess the differences among the five team members, a Kruskal–Wallis test was done as shown in Tables 7.2 and 7.3. The results of the respective 35 variables of interest showed that there is no statistically significant difference between the group mean rank as all the significance values are above 0.05, except for six variables (LP3, LP4, LP6, LP7, CW1 and CW2) which are indicated in asterisks. As such, differences in the views among the five team members as well as non-response of the remaining 45 (or 28%) team members could be taken to be irrelevant in this study. This is because the Kruskal–Wallis test showed that the non-responses of these team members—Architectural Coordinator, M&E Coordinator and Precaster’s Representative will likely not affect the analysis. Such differences in six of the variables could be explained due to the varying levels of involvement by each team member in the respective precast construction process. This is supported by Mr. E (main contractor) who mentioned that. …team members typically only take care of their own areas and would not have time to be aware of and understand the issues in the actual activities. They may not know where the wastes can be cut and which work activities have potential for man-days to be optimised.

In the implementation of lean construction principles, it is key that the project manager drives this practice within the team to result in minimisation of construction wastes and the total man-days utilisation. The project manager is the leader of the construction project and usually have more experience than the rest of the team. He or she would be in the position to know the tasks to be done and direct the team to implement such that maximum reduction in the occurrence of construction wastes and total man-days utilisation could be achieved. Hence, the mean rank by the project manager is generally higher than the rest of the team members. The other team members could have taken instructions from the project manager and may or may not be aware of the intentions behind his or her actions. Mr. C (precaster) asserted that these team members. …should be aware and will want to work together collaboratively and practice lean…they definitely understand the situation, especially the experienced ones, though may have difficulties practicing it due to the client’s design, cost, regulations, etc.

Therefore, it is recommended that the project manager or the organisation educate and train their staffs so that they are able to perform their job competently as well as understand the rationale of doing things in a certain approach (Liker and Convis 2012). This will enable them to strive to reduce the occurrence of construction wastes and minimise the total man-days to be utilised at all stages of the precast construction process.

104

7 Results and Analysis

Table 7.2 Mean rank of each team member Team member LP1

LP2

LP3*

LP4*

LP5

LP6*

N

Mean rank

Project Manager

32

58.30

Site Structural Engineer

32

55.59

Architectural Coordinator

18

56.92

M&E Coordinator

17

68.68

Precaster’s Representative

16

52.09

Total

115

Project Manager

32

58.44

Site Structural Engineer

32

60.75

Architectural Coordinator

18

63.56

M&E Coordinator

17

52.35

Precaster’s Representative

16

51.38

Total

115

Project Manager

32

69.13

Site Structural Engineer

32

60.80

Architectural Coordinator

18

40.64

M&E Coordinator

17

53.91

Precaster’s Representative

16

54.03

Total

115

Project Manager

32

70.25

Site Structural Engineer

32

45.45

Architectural Coordinator

18

60.17

M&E Coordinator

17

53.53

Precaster’s Representative

16

60.91

Total

115

Project Manager

32

56.05

Site Structural Engineer

32

62.28

Architectural Coordinator

18

72.56

M&E Coordinator

17

45.74

Precaster’s Representative

16

50.00

Total

115

Project Manager

32

55.61

Site Structural Engineer

32

67.69

Architectural Coordinator

18

68.25

M&E Coordinator

17

50.35

Precaster’s Representative

16

40.00

Total

115 (continued)

7.3 Analysis of Variance

105

Table 7.2 (continued) Team member LP7*

LP8

LP9

LP10

LP11

LP12

N

Mean rank

Project Manager

32

52.84

Site Structural Engineer

32

64.75

Architectural Coordinator

18

73.00

M&E Coordinator

17

55.79

Precaster’s Representative

16

40.28

Total

115

Project Manager

32

59.28

Site Structural Engineer

32

61.44

Architectural Coordinator

18

57.92

M&E Coordinator

17

46.94

Precaster’s Representative

16

60.41

Total

115

Project Manager

32

64.06

Site Structural Engineer

32

51.34

Architectural Coordinator

18

54.17

M&E Coordinator

17

54.53

Precaster’s Representative

16

67.19

Total

115

Project Manager

32

56.77

Site Structural Engineer

32

58.63

Architectural Coordinator

18

71.72

M&E Coordinator

17

61.65

Precaster’s Representative

16

39.91

Total

115

Project Manager

32

54.38

Site Structural Engineer

32

57.34

Architectural Coordinator

18

58.97

M&E Coordinator

17

70.12

Precaster’s Representative

16

52.59

Total

115

Project Manager

32

61.33

Site Structural Engineer

32

56.16

Architectural Coordinator

18

51.58

M&E Coordinator

17

52.06

Precaster’s Representative

16

68.56

Total

115 (continued)

106

7 Results and Analysis

Table 7.2 (continued) Team member LP13

LP14

SMM1

SMM2

SMM3

SMM4

N

Mean rank

Project Manager

32

59.91

Site Structural Engineer

32

52.69

Architectural Coordinator

18

64.11

M&E Coordinator

17

53.15

Precaster’s Representative

16

63.09

Total

115

Project Manager

32

64.42

Site Structural Engineer

32

55.41

Architectural Coordinator

18

48.36

M&E Coordinator

17

56.71

Precaster’s Representative

16

62.56

Total

115

Project Manager

32

66.67

Site Structural Engineer

32

57.52

Architectural Coordinator

18

47.50

M&E Coordinator

17

57.21

Precaster’s Representative

16

54.28

Total

115

Project Manager

32

56.53

Site Structural Engineer

32

55.61

Architectural Coordinator

18

56.89

M&E Coordinator

17

61.68

Precaster’s Representative

16

63.06

Total

115

Project Manager

32

58.41

Site Structural Engineer

32

56.94

Architectural Coordinator

18

55.78

M&E Coordinator

17

55.71

Precaster’s Representative

16

64.25

Total

115

Project Manager

32

64.44

Site Structural Engineer

32

54.23

Architectural Coordinator

18

60.28

M&E Coordinator

17

49.65

Precaster’s Representative

16

58.97

Total

115 (continued)

7.3 Analysis of Variance

107

Table 7.2 (continued) Team member SMM5

SMM6

SMM7

SMM8

SMM9

SMM10

N

Mean rank

Project Manager

32

57.58

Site Structural Engineer

32

62.39

Architectural Coordinator

18

49.36

M&E Coordinator

17

54.38

Precaster’s Representative

16

63.63

Total

115

Project Manager

32

63.36

Site Structural Engineer

32

62.38

Architectural Coordinator

18

53.50

M&E Coordinator

17

50.62

Precaster’s Representative

16

51.44

Total

115

Project Manager

32

61.95

Site Structural Engineer

32

63.66

Architectural Coordinator

18

61.47

M&E Coordinator

17

44.82

Precaster’s Representative

16

48.88

Total

115

Project Manager

32

62.28

Site Structural Engineer

32

59.95

Architectural Coordinator

18

54.08

M&E Coordinator

17

53.00

Precaster’s Representative

16

55.25

Total

115

Project Manager

32

63.95

Site Structural Engineer

32

61.64

Architectural Coordinator

18

55.61

M&E Coordinator

17

51.29

Precaster’s Representative

16

48.63

Total

115

Project Manager

32

67.75

Site Structural Engineer

32

53.23

Architectural Coordinator

18

58.92

M&E Coordinator

17

58.38

Precaster’s Representative

16

46.59

Total

115 (continued)

108

7 Results and Analysis

Table 7.2 (continued) Team member CW1*

CW2*

CW3

CW4

CW5

CW6

N

Mean rank

Project Manager

32

60.67

Site Structural Engineer

32

68.42

Architectural Coordinator

18

52.67

M&E Coordinator

17

49.76

Precaster’s Representative

16

46.56

Total

115

Project Manager

32

65.98

Site Structural Engineer

32

66.22

Architectural Coordinator

18

49.72

M&E Coordinator

17

47.21

Precaster’s Representative

16

46.38

Total

115

Project Manager

32

55.31

Site Structural Engineer

32

59.47

Architectural Coordinator

18

61.83

M&E Coordinator

17

61.35

Precaster’s Representative

16

52.56

Total

115

Project Manager

32

57.47

Site Structural Engineer

32

56.66

Architectural Coordinator

18

58.00

M&E Coordinator

17

57.41

Precaster’s Representative

16

62.38

Total

115

Project Manager

32

59.59

Site Structural Engineer

32

52.25

Architectural Coordinator

18

65.67

M&E Coordinator

17

58.53

Precaster’s Representative

16

57.13

Total

115

Project Manager

32

58.47

Site Structural Engineer

32

56.98

Architectural Coordinator

18

61.47

M&E Coordinator

17

55.85

Precaster’s Representative

16

57.47

Total

115 (continued)

7.3 Analysis of Variance

109

Table 7.2 (continued) Team member CW7

CW8

CW9

CW10

CW11

N

Mean rank

Project Manager

32

62.89

Site Structural Engineer

32

53.39

Architectural Coordinator

18

57.56

M&E Coordinator

17

55.06

Precaster’s Representative

16

61.06

Total

115

Project Manager

32

58.80

Site Structural Engineer

32

55.56

Architectural Coordinator

18

60.56

M&E Coordinator

17

58.26

Precaster’s Representative

16

58.13

Total

115

Project Manager

32

59.25

Site Structural Engineer

32

63.09

Architectural Coordinator

18

56.97

M&E Coordinator

17

53.50

Precaster’s Representative

16

51.25

Total

115

Project Manager

32

60.06

Site Structural Engineer

32

56.55

Architectural Coordinator

18

58.47

M&E Coordinator

17

67.41

Precaster’s Representative

16

46.25

Total

115

Project Manager

32

54.33

Site Structural Engineer

32

56.13

Architectural Coordinator

18

65.22

M&E Coordinator

17

62.41

Precaster’s Representative

16

56.28

Total

115

110 Table 7.3 Results of Kruskal–Wallis test

7 Results and Analysis Variables

Chi-square

df

Asymp. Sig

LP1

2.586

4

0.629

LP2

2.030

4

0.730

LP3

9.890

4

0.042*

LP4

10.039

4

0.040*

LP5

8.179

4

0.085

LP6

10.877

4

0.028*

LP7

10.980

4

0.027*

LP8

2.526

4

0.640

LP9

4.279

4

0.370

LP10

8.600

4

0.072

LP11

3.350

4

0.501

LP12

3.557

4

0.469

LP13

2.509

4

0.643

LP14

3.588

4

0.465

SMM1

4.663

4

0.324

SMM2

0.939

4

0.919

SMM3

0.885

4

0.927

SMM4

3.095

4

0.542

SMM5

2.693

4

0.610

SMM6

3.579

4

0.466

SMM7

5.949

4

0.203

SMM8

1.532

4

0.821

SMM9

3.882

4

0.422

SMM10

5.920

4

0.205

CW1

9.698

4

0.046*

CW2

11.651

4

0.020*

CW3

1.472

4

0.832

CW4

0.397

4

0.983

CW5

2.495

4

0.646

CW6

0.383

4

0.984

CW7

1.892

4

0.756

CW8

0.355

4

0.986

CW9

2.237

4

0.692

CW10

4.538

4

0.338

CW11

2.017

4

0.733

7.4 Data Understanding

111

7.4 Data Understanding 7.4.1 Lean Principles and Shared Mental Models The descriptive statistics of the 24 attributes resulting in reduction in occurrence of construction wastes are shown in Table 7.4. It is gathered that the top three attributes resulting in reduction in occurrence of construction wastes during the precast construction process are based on the lean principles, namely—‘Create continuous process flow to bring problems to the surface’ (LP2), ‘Build a culture of stopping to fix problems, to get quality right the first time’ (LP5), and ‘Focus on long-term results’ (LP1). These three attributes were generally found to result in between 20 to 40% reduction in the occurrence of construction wastes during the precast construction process. For LP2, respondents experienced higher reduction in construction wastes when the process requires them to stop work whenever problem occurs. This shows that having a process in place to check and bring problems to the surface for rectification is critical before allowing the process to continue. Mr. C (precaster) cited that. …our draftsmen will do up the shop drawings, then our engineers will check to ensure compliance with the consultants drawings. If this process is not in place, we would have big problem during production as once the shop drawings are used for production, the rectification later on, if anything is found to be wrong, would be very tough.

For LP5, respondents experienced higher reduction in construction wastes when they stop the work upon discovering any problem till it is resolved and ensure that the problem would not recur to get quality right the first time. With reference to this, both Mr. A (precaster) and Mr. B (main contractor) believe that the quality of precast components at the precaster’s factory is important which ideally should have been audited to meet certain quality standards and there should also be proper factory supervision to ensure that things are done correctly. For LP1, respondents experienced higher reduction in construction wastes when they think ahead rather than looking at short-term gains in their decision making process. Both Mr. C (precaster) and Mr. E (main contractor) opined that this would be challenging as contractors must be willing to invest in resources to do so. Fundamentally, the construction industry is alien to the use of technologies which is key to reduce construction wastes. Moreover, many senior people in the construction industry are very experienced and knowledgeable but their speed of picking up such new technologies and lean approaches may be much slower. Nonetheless, Mr. D (main contractor) is of the view that. As the main contractor, it is to our advantage to think long-term as we will be affected in the end, being the main party responsible to the client.

Hence, it is important that top management direction and support is provided to team members so that they develop a consistent sense of purpose and are aligned with the intended process flow and outcomes when performing their tasks.

112

7 Results and Analysis

Table 7.4 Descriptive statistics of attributes resulting in reduction in occurrence of construction wastes Label

Attributes resulting in reduction in occurrence of construction wastes

Mean

Standard deviation

LP2

Create continuous process flow to bring problems to the surface 5.452

0.948

LP5

Build a culture of stopping to fix problems, to get quality right the first time

5.452

0.920

LP1

Focus on long-term results

5.443

1.141

LP7

Use visual control throughout the process so no problems are hidden

5.417

1.124

SMM3

Team members share information that is previously possessed individually by each team member to others in the team

5.383

0.960

LP3

Use “Pull” systems to avoid overproduction

5.374

1.013

LP6

Standardise tasks as a foundation for continuous improvement

5.304

1.069

LP10

Develop your people

5.304

1.141

SMM4

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

5.287

0.925

SMM7

Team members collaborate and work closely through a structured means of communication

5.261

1.060

LP11

Grow together with solid subcontractors and suppliers

5.261

1.035

LP8

Adapt operations to suit technology, people and processes

5.252

1.067

SMM1

Team members reconcile conflicts and reconfirm goals

5.235

0.872

SMM9

Cross-training to equip team members with a shared knowledge 5.183 of their teammates’ work

0.894

SMM6

Team members have a common goal and form compatible expectations to act accordingly

5.122

0.860

SMM10

Team members get another’s information requirement accurately and quickly

5.078

0.860

SMM8

Team members are committed and motivated to meet the client’s needs

5.026

0.912

LP9

Empower your people

4.983

1.076

LP13

Make decisions slowly by consensus, thoroughly considering all options and implement decisions rapidly

4.939

0.891

LP14

Review processes for continuous improvement

4.930

0.845

LP12

Go and see for yourself to thoroughly understand the situation

4.913

1.005

SMM5

Team members integrate information and determine the consequences

4.835

0.878

SMM2

Team members develop introspective practices

4.748

0.826

LP4

Level out the workload

4.696

1.110

7.4 Data Understanding

113

It is noted that the standard deviation for the 24 attributes resulting in reduction in occurrence of construction wastes is relatively high which means that the values in the dataset are, on average, further away from the mean. This is expected given that respondents have worked on different projects of varying complexity and demands. In each project, respondents work with different team members and have to realign themselves to jointly establish their lean approach and develop their shared mental models. As such, the reduction in the occurrence of construction wastes would likely differ depending on their project experience as well as the team’s experience. For example, the more experienced team members could have already learnt from their past precast construction projects and able to make improvements to result in significant reduction in the occurrence of construction wastes. To test the reliability of these 24 attributes, the Cronbach’s alpha of the 24 attributes resulting in reduction in occurrence of construction wastes was calculated which gave a figure of 0.778. Results of Cronbach’s alpha range from 0 to 1 and the closer its value to 1, the higher its reliability which indicates that all variance in this set of items is highly consistent (Cortina 1993). According to Blunch (2013), the high level of agreement (Corrected item-total correlation > 0.40 and Cronbach’s alpha > 0.70) between the respondents’ experience in the amount of reduction in the occurrence of construction wastes during the precast construction process resulting from implementation of the 24 attributes strongly supports their relevance in this study. The Cronbach’s alpha improved slightly when one of the attributes (indicated in asterisks) was deleted as shown in Table 7.5. On top of that, the corrected itemtotal correlation of this attribute is lower compared to the remaining 23 attributes. Hence, this attribute—‘Use visual control throughout the process so no problems are hidden’ is relatively inconsistent for the interpretation of the reduction in the occurrence of construction wastes during the precast construction process. However, the high mean value of this attribute at rank number four still shows the importance of its implementation to reduce the occurrence of construction wastes. The inconsistent responses could be because some team members are not looking into visualising the entire precast construction process. In a construction project, there are multiple disciplines—architectural, civil, structural, M&E and other specialists which must work collaboratively. At the front-end stage, the civil and structural discipline, whose works start first, may have designed and planned without due considerations of the other disciplines. In addition, the other disciplines may not have started planning their design and routing to check through if there are any clashes with the structural components. By and large, the focus of each individual tends to be their own discipline, but it is important that everybody is able to take into consideration all aspects as there are many technical interfaces which have to be properly coordinated (Van den Bossche et al. 2011). For example, Mr. D (main contractor) explained that. …to improve the buildability score…we do not just leave it to the consultants to design based on the minimum requirement. Same for constructability, we also discuss with the consultants on what items to do.

114

7 Results and Analysis

Table 7.5 Convergent validity analysis of attributes resulting in reduction in occurrence of construction wastes Label

Attributes resulting in reduction in occurrence of construction wastes

Corrected item-total correlation

Cronbach’s alpha if item deleted

LP1

Focus on long-term results

0.212

0.777

LP2

Create continuous process flow to bring problems to the surface 0.304

0.771

LP3

Use “Pull” systems to avoid overproduction

0.772

LP4

Level out the workload

0.215

0.776

LP5

Build a culture of stopping to fix problems, to get quality right the first time

0.379

0.767

LP6

Standardise tasks as a foundation for continuous improvement

0.283

0.772

LP7

Use visual control throughout the process so no problems are hidden

0.161

0.780*

LP8

Adapt operations to suit technology, people and processes

0.180

0.778

LP9

Empower your people

0.198

0.777

LP10

Develop your people

0.369

0.767

LP11

Grow together with solid subcontractors and suppliers

0.402

0.765

LP12

Go and see for yourself to thoroughly understand the situation

0.411

0.764

LP13

Make decisions slowly by consensus, thoroughly considering all options and implement decisions rapidly

0.385

0.766

LP14

Review processes for continuous improvement

0.516

0.760

SMM1

Team members reconcile conflicts and reconfirm goals

0.352

0.768

SMM2

Team members develop introspective practices

0.270

0.772

SMM3

Team members share information that is previously possessed individually by each team member to others in the team

0.292

0.771

SMM4

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

0.165

0.778

SMM5

Team members integrate information and determine the consequences

0.376

0.767

SMM6

Team members have a common goal and form compatible expectations to act accordingly

0.436

0.764

SMM7

Team members collaborate and work closely through a structured means of communication

0.330

0.769

SMM8

Team members are committed and motivated to meet the client’s needs

0.389

0.766

SMM9

Cross-training to equip team members with a shared knowledge of their teammates’ work

0.410

0.765

SMM10

Team members get another’s information requirement accurately and quickly

0.391

0.766

0.273

7.4 Data Understanding

115

Team members need to be convinced that the quality built-in with visualisation of the entire precast construction process for waste elimination are beneficial in the long run. With that, they should be able to foresee downstream problems and take immediate action to prevent the occurrence of construction wastes.

7.4.2 Changes in Man-Days The descriptive statistics of the 11 attributes resulting in changes in man-day used are shown in Table 7.6. The top attribute resulting in the highest reduction in the manpower utilisation during the precast construction process is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’. This Table 7.6 Descriptive statistics of attributes resulting in changes in man-day used Label

Attributes resulting in changes in manpower Used

Mean Standard deviation

CW1

Minimisation of defects and rework due to incompatibility of design 5.104 0.693 with downstream precast construction processes

CW2

Minimisation of extra-processing due to design changes

5.070 0.710

CW4

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

4.791 0.800

CW3

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

4.739 0.727

CW9

Minimisation of non-utilised resources due to the lack of knowledge 4.626 0.668 sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

CW10 Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

4.609 0.722

CW7

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

4.583 0.701

CW8

Minimisation of motion from the arrival of precast components at site to hoisting

4.574 0.714

CW6

Minimisation of non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

4.496 0.730

CW11 Minimisation of overproduction due to the lack of accurate planning 4.478 0.718 preparations in precast construction causing extra-processing CW5

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

4.470 0.717

116

7 Results and Analysis

is because if things are not done right from the start, the downstream reworks and correction action required would be tremendous. Mr. D (main contractor) noted that. …during design till the first structure production…everybody have to coordinate, think ahead and be committed on the project…we will work together with the consultants to explore how to standardise as far as possible.

Mr. A (precaster) concurred and highlighted that a precaster’s work would be more complicated and more man-effort is required if the design is not standardised. Mr. A (precaster) revealed that this is because. We are usually brought into the project quite late. Ideally, our detailing inputs should be sought six months before the production schedule.

This corresponds with the lean principle on ‘Build a culture of stopping to fix problems, to get quality right the first time’. This is also evident from the interviewees who understood that the flipside of precast construction was an extended upfront design period but they agreed that there would be manpower savings eventually. The second attribute resulting in the highest reduction in the manpower utilisation during the precast construction process is ‘Minimisation of extra-processing due to design changes’. This refers to unnecessary processes arising from changes in design that serves to enhance the end-user’s workflow experience, changes in client’s requirement which require a re-design and changes due to coordination issues with the various disciplines. Therefore, the reduction in the manpower utilisation in the precast construction process could be substantial if all these extra-processing efforts are eliminated. Client-initiated design changes that cropped up may be beneficial to the end user during the operation and maintenance stage but will lead to additional man-effort in which the quantum will depend on the progress of the construction and extent of changes required. Mr. E (main contractor) was the only interviewee who raised that design changes which are initiated by the client should not be considered as construction wastes. For example, the client may request for additional toilets at a certain location in the building. As such, there is a need to design and construct the sanitary and plumbing services to this new location. At the same time, team members will have to check and assess the impact of this change to the overall design. Moreover, Mr. C (precaster) voiced that sufficient reaction time is required for team members to react regardless of the cause of design changes or there would be extra-processing. To be more precise, it is still deemed that design changes should include client-initiated changes as there would be an impact to the eventual man-days utilised. The third attribute resulting in the highest reduction in the manpower utilisation during the precast construction process is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. B (main contractor) cited that this happens as. …precaster typically prefers to complete the casting for all same type of components at one go for efficiency. If this is the case, the precaster would have to have a holding area at their precast yard to store these precast components first as the site would not have space for early delivery of these items.

7.4 Data Understanding

117

Mr. B (main contractor) stated that. …two-way communication is required to work out a win-win solution for both parties.

Mr. C (precaster) also mentioned that. We typically discuss the construction schedule with the contractor and produce accordingly.

Furthermore, Mr. E (main contractor) opined that. This is an error, wrong arrangement of work leading to inventory and fats. Though we have done value stream mapping to work out the sequence, somehow, there are communication issues which resulted in this scenario…was not properly cascaded down to the subcontractor, supervisors and workers. End up, we now have lesser working space to continue with the production.

Therefore, to minimise such instances, there should be an organised continuous process flow in place to meet the JIT concept to lower inventory. This should be followed through in the subsequent logistics and installation stages. To test the reliability of these 11 attributes, the Cronbach’s alpha of the 11 attributes resulting in changes in total manpower used during the precast construction process was calculated which gave a figure of 0.903. The high level of agreement between the respondents’ experience in the extent of changes in the total man-days used during the precast construction process resulting from minimisation of the construction wastes strongly supports their relevance in this study. Moreover, the Cronbach’s alpha did not improve when the 11 attributes were deleted as shown in Table 7.7 which means that none of these attributes are inconsistent for the interpretation of the changes in the manpower used on-site and off-site during the precast construction process. This is further supported based on the fact that the average standard deviation for the 11 attributes resulting in reduction in changes in the total man-days used at 0.718 is relatively lower than the average standard deviation for the 24 attributes resulting in reduction in the changes in the occurrence of construction wastes at 0.976. This suggests that the values in the dataset for the 11 attributes resulting in changes in the manpower utilisation in precast construction are, on average, closer to the mean. This could be because it is more quantifiable to assess changes in the total man-days utilisation as compared to changes in the occurrence of construction wastes.

7.4.3 Strength of Dependence Between Reduction of Construction Wastes and Manpower Changes The Spearman rank-order correlation coefficient (ρ) is used to determine the strength of dependence of the following three pairs of relationships and tests Hypotheses 1– 3. The bias corrected and accelerated (BCa) bootstrapped confidence interval based on simple random sampling was also done as significance values may be affected by the distribution of the responses. Bootstrapping is about estimating the sampling

118

7 Results and Analysis

Table 7.7 Convergent validity analysis of attributes resulting in changes in manpower used Label

Attributes resulting in changes in manpower used

Corrected Cronbach’s item-total alpha if correlation item deleted

CW1

Minimisation of defects and rework due to incompatibility of 0.550 design with downstream precast construction processes

0.899

CW2

Minimisation of extra-processing due to design changes

0.541

0.900

CW3

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

0.501

0.902

CW4

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

0.700

0.891

CW5

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

0.713

0.890

CW6

Minimisation of non-utilised resources due to incompetency 0.673 of workforce to perform precast construction causing defects and rework

0.892

CW7

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

0.745

0.889

CW8

Minimisation of motion from the arrival of precast components at site to hoisting

0.727

0.889

CW9

Minimisation of non-utilised resources due to the lack of 0.606 knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

0.896

CW10 Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

0.632

0.895

CW11 Minimisation of overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

0.664

0.893

distribution of an estimator by sampling with replacement from the original sample whereby every respondent from the original sample is again eligible to be selected regardless if this respondent has already been selected. The BCa bootstrap method incorporates information on bias and change in standard error of the estimator into the estimation procedure. The BCa confidence interval is the boundary between which the population value falls in 95% of the samples. If the interval crosses zero, it means that there could be no relationship or negative relationship or positive relationship. If the interval does not cross zero, it means that there is either a positive or negative relationship. The results are shown in Table 7.8. The correlation coefficient of the reduction of construction wastes due to the implementation of lean principles is 0.341 with shared mental models development. The significance values of both correlation coefficients are all less than 0.05 based on

Lean principles (LP1–LP14)

Lean principles (LP1–LP14)

Shared mental models (SMM1–SMM10)

H1: The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction of construction wastes due to the development of shared mental models

H2: The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction in the total man-days used in precast construction

H3: The reduction of construction wastes due to the development of shared mental models would have a positive effect on the reduction in the total man-days used in precast construction

Manpower changes (CW1–CW11)

Manpower changes (CW1–CW11)

Shared Mental Models (SMM1–SMM10)

Factor 2

0.341**

H0 : ρ = 0 H1 : ρ = 0

0.330**

0.220*

Correlation coefficient

Test

*Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed) a Unless otherwise noted, bootstrap results are based on 1000 bootstrap samples

Factor 1

Hypothesis

Table 7.8 Spearman rank-order correlation coefficient tests for manpower changes

0.000

0.018

0.000

Sig. (2-tailed)

0.088

0.092

−0.001

0.000

0.085

Std. error

−0.005

Bias

Bootstrapa

0.142–0.499

0.029–0.394

0.162–0.495

BCa 95% confidence interval

7.4 Data Understanding 119

120

7 Results and Analysis

a two-tailed test which means that the probability of getting a correlation coefficient at this value if the null hypotheses were true is very low. The BCa confidence interval of the relationship between lean principles and shared mental models is 0.162–0.495, which does not cross zero. This means that there is a significant positive relationship between the reduction of construction wastes due to the implementation of lean construction principles and the reduction of construction wastes due to the development of shared mental models during the precast construction process. Therefore, Hypothesis 1 is supported. The low correlation coefficient was explained by Mr. B (main contractor) who stated that. …if a certain portion of work cannot be done, the next work cannot start and there is a need to inform everybody and work out the revised design and approach…many of the things are done just-in-time, just like lean, sometimes, it is too late by the time the information is passed down.

This corresponds with the lean principle on “build a culture of stopping to fix problems, to get quality right the first time” and shared mental model on “team members collaborate and work closely through a structured means of communication”. This implies that both lean principles and shared mental models are important and play a part in contributing to the reduction of construction wastes during the precast construction process. Furthermore, Stoyanova and Kommers (2002) also concluded that intense collaboration, and not just knowing about the technicalities, propelled the development of the solution and enhanced the effectiveness of getting to the optimal outcome. The low strength of dependence could be because some respondents felt that as different team members work together to deliver the precast construction project, more time is required for them to first develop shared mental models. This process contributes to the occurrence of construction wastes before they are able to effectively apply lean principles to result in the reduction of construction wastes. Moreover, Mr. A (precaster) mentioned that this could also be because. People always think that they still have time to work on it later on, during the next coordination meeting for example, when they are pressed for an answer. When they want to act on it and think of alternative solutions for example, it may be too late.

The correlation coefficient of the reduction of construction wastes due to the implementation of lean principles is 0.220 with manpower changes. The BCa confidence interval of the relationship between lean principles and manpower changes is 0.029–0.394, which also does not cross zero. This means that there is a significant positive relationship between the changes in the occurrence of construction wastes due to the implementation of lean construction principles and the changes in the total man-days used in precast construction. Therefore, Hypothesis 2 is supported. Moreover, such repetitive work creates an opportunity for team members to get themselves organised and lead to the production and installation of precast components of higher quality. The low strength of dependence could be because some respondents felt that the reduction in the occurrence of construction wastes with the

7.4 Data Understanding

121

application of lean principles may not necessarily result in an observable reduction in the total manpower effort required. This was also explained by Mr. F (precaster) who said that. By nature, precast is still very labour-intensive. I think the total man-days would not reduce significantly unless precision engineering is adopted which would be much more costly.

A key aspect of enabling lean in precast construction is about carrying out due diligence upfront by considering the implications from the design, production, logistics and installation stages, so as to eliminate design deficiencies and reworks in the later stages. This requires manpower effort to do tasks such as quality control and assurance and hence, the overall reduction in the man-days may not be noticeable to some team members. The correlation coefficient of the reduction of construction wastes due to the development of shared mental models and the extent of manpower changes is 0.330 is significant based on both the two-tailed and BCa confidence interval tests. This shows that the reduction of construction wastes due to the development of shared mental models would have an effect on the reduction in the total man-days used during the precast construction process. Therefore, Hypothesis 3 is supported. The low correlation coefficient was explained by Mr. C (precaster) who shared that there is a limit as to how much the development of shared mental models will lead to reduction in the total man-days as the project design comes into play too and not just about the team performance. Mr. C (precaster) cited an example that more man-effort would be incurred for design of more variants as more inspections would be required. In addition, El-Gohary and Aziz (2013) also explained that the development of shared mental models is very much dependent on the attitude of each individual person. If the people are not motivated and eager to make a difference to improve the precast productivity performance, they will not achieve the maximum reduction in the total manpower effort used. Jonker et al. (2011) rationalised that team members have to recognise that the mental model increases coherence in order for them to be committed and shift to the new shared mental model to result in high practical utility. Respondents acknowledged that the optimisation of manpower requirements can be made using a mental model that has worked well even in teams without prior history of collaborating. This shows that it is important to get buy-in from the workers, educate them about the benefits of precast construction compared to the traditional cast in-situ construction approach and also involve them to optimise their work processes and reduce the occurrence of construction wastes as they carry out the work (Alagaraja 2014). Having a shared mental model is important as it can also lead team members to overcome obstacles in building team norms and consensus which then enhances support and commitment during the precast construction process (Rouse et al. 1992). The construct of shared mental models can serve as a framework in which successful teamwork is understood, and specific predictions about the project performance can be generated.

122

7 Results and Analysis

7.5 Data Preparation 7.5.1 Leading Indicator of Precast Productivity Performance Leading indicators can give an initial sense of the anticipated construction productivity outcome and prompt for actions to be taken. This creates an opportunity for improvements to be made resulting in lesser construction wastes and added value for the project. Leading indicators can also pre-empt on the adequacy of the controls and processes and influence the contractor to make necessary improvements to ensure better productivity (Shen and Zhou 2014). The leading indicator in this study measures the contractor’s ability to manage precast construction projects in a lean environment, which covers minimisation of construction wastes to reduce the mandays utilised. The leading indicator is constructed by classifying the distribution of the changes in the occurrence of construction wastes due to the lean principles and shared mental models development and total changes in manpower used into two distinct tiers as shown in Table 7.9. Based on the data understanding, this study deemed that responses which fall above or equal to the approximate mean rating of 5 for each of the three broad factors—Lean Principles, Shared Mental Models and Manpower Changes, are classified as low risk (“Above Threshold”). Responses which fall below the approximate mean rating of 5 for each of the three broad factors are classified as high risk (“Below Threshold”). To emphasise, the intent of this study is to point out to the team members involved in the precast construction project of the risk of their productivity performance. This is because team members who are not in the know cannot employ effective lean construction strategies and ineffective lean implementation can lead to minimal reduction in the occurrence of construction wastes. Hence, only two categories were specified. The key is to point out to contractors that they are “Below Threshold” so that they can make timely effort in the reduction of construction wastes and optimise their manpower effort. Further checks were done to ascertain the classification of the data into the two tiers. 46% of the responses are classified as “Above Threshold” and 54% of the responses are classified as “Below Threshold” which are about the same. Hence, there Table 7.9 Classification into leading indicator of precast productivity performance S/N

Leading indicator of precast productivity performance

LP1–LP14

SMM1–SMM10

CW1–CW11

Count

Proportion (%)

1

Above threshold [1]

≥5

≥5

≥5

53

46

2

Below threshold [0]

Remaining datasets which does not fulfil the above requirement

62

54

7.5 Data Preparation

123

Fig. 7.5 Boxplot of leading indicator of precast productivity performance against changes in the occurrence of construction wastes due to lean construction implementation

Fig. 7.6 Boxplot of leading indicator of precast productivity performance against changes in the occurrence of construction wastes due to development of shared mental models

124

7 Results and Analysis

Fig. 7.7 Boxplot of leading indicator of precast productivity performance against changes in the manpower utilisation

is no unequal representation or class imbalance dataset which may have detrimental effect to the learning performance of the under-represented classes. The boxplots of the respective leading indicators against the three broad factors indicate that there is a slight noticeable distribution among the two outcomes as shown in Figs. 7.5, 7.6 and 7.7. Investigation showed that some of the outliers were not due to systematic errors. This is because the dataset come from respondents from different organisations and it is noted that each organisation practice lean construction differently and varying degree of shared mental models will be developed among the team members working on the precast construction project. There are also different challenges when managing different precast construction projects and hence the implementation of lean construction and development of shared mental models will result in varying reduction in the occurrence of construction wastes. Hence, these outliers were not removed.

7.5.2 Relationship Between Reduction of Construction Wastes and Leading Indicator of Precast Productivity Performance The Spearman rank-order correlation coefficient (ρ) is done to study the degree of association for the two pairs of relationships and tests Hypotheses 4 and 5. Similarly,

7.5 Data Preparation

125

the BCa bootstrapped confidence interval was also done to ascertain that the significance values would not be affected by the distribution of responses. The results are shown in Table 7.10. The relationship of the reduction of construction wastes due to the implementation of lean construction principles with the leading indicator of precast productivity performance gave a slightly stronger correlation coefficient at 0.350 as compared to with the manpower changes at 0.220. This is expected given that the leading indicator of precast productivity performance was partly derived from the lean principles and manpower changes. The correlation coefficient of the reduction of construction wastes due to the implementation of lean principles and its leading indicator of precast productivity performance is significant based on both the two-tailed and BCa confidence interval tests. This shows that there is a significant positive relationship between the leading indicator of precast productivity performance and the reduction of construction wastes due to the implementation of lean construction principles. Therefore, Hypothesis 4 can also be supported. Similarly, the relationship of the reduction of construction wastes due to the development of shared mental models with the leading indicator of precast productivity performance gave a slightly stronger correlation coefficient at 0.546 as compared to with the manpower changes at 0.330. This is expected given that the leading indicator of precast productivity performance was partly derived from the shared mental models and manpower changes. This correlation coefficient is significant based on both the two-tailed and BCa confidence interval tests. This means that the reduction of construction wastes due to the development of shared mental models would have an effect on the leading indicator of precast productivity performance. Therefore, Hypothesis 5 is supported. The results showed that the correlation coefficient of the leading indicator of precast productivity performance with the development of shared mental models is higher than with the implementation of lean principles. Studies have acknowledged the importance of shared mental models to produce substantial results especially when team members are scattered across different organisations which is the norm for construction projects (Hosseini et al. 2018; Fransen et al. 2011). With the lack of a history of cooperation among team members, this explains the importance of developing shared mental models to result in higher precast productivity performance. This means that the notion of shared mental models is valuable to understand the cognitive components of team performance. This suggests changes in the development of shared mental models will have a greater impact on the leading indicator of precast productivity performance than changes in the implementation of lean principles. As this leading indicator was not put into practice, most of the interviewees could not differentiate the impact due to the development of shared mental models or lean construction implementation. In particular, five of the interviewees raised the following concerns as summarised in Table 7.11. To ascertain the accuracy of the model predictive ability as well as the relevance of the 24 lean construction and shared mental model attributes as inputs to determine the precast productivity performance, validation of the neural network model on an actual case study is required which would be discussed in Chap. 8.

Leading Indicator of Precast Productivity Performance

Leading Indicator of Precast Productivity Performance

H4: The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the implementation of lean construction principles

H5: The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the development of shared mental models

Shared Mental Models

Lean Principles

Factor 2

0.350**

H0 : ρ = 0 H1 : ρ = 0

0.546**

Correlation coefficient

Test

*Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed) a Unless otherwise noted, bootstrap results are based on 1000 bootstrap samples

Factor 1

Hypothesis

0.000

0.000

Sig. (2-tailed)

0.001

−0.002

Bias

Bootstrapa

Table 7.10 Spearman rank correlation coefficient tests for leading indicator of precast productivity performance

0.066

0.080

Std. error

0.405–0.678

0.194–0.492

BCa 95% confidence interval

126 7 Results and Analysis

7.5 Data Preparation

127

Table 7.11 Concerns about the leading indicator for precast productivity performance S/N Interviewee

Concerns

1

Mr. A (precaster)

“this can only be used as a guide as the figures are unlikely to be accurate, just like BCA’s site productivity figures…not accurately accounted to the correct category of work…”

2

Mr. B (main contractor) “this seems to rely on the team member’s self-assessment which may be one-sided…”

3

Mr. C (precaster)

4

Mr. D (main contractor) “…may be hard to measure…”

5

Mr. E (main contractor) “…we need to have some means to track where we are as the project progresses, even for different disciplines and trades…”

6

Mr. F (precaster)

No concerns were raised

“…not sure if the leading indicator would be reflective if it is done too early…”

Nevertheless, the need and usefulness of this leading indicator for precast productivity performance was supported by all six interviewees. In particular, Mr. E (main contractor) said that this leading indicator, being a qualitative measure, …is in the right direction as a quantitative indicator would be hard to implement…just too time-consuming and not worth the effort.

In summary, responses which are “Above Threshold” are likely to have practiced lean construction principles and shared mental models development to a larger extent, resulting in the reduction of construction wastes and lower man-days utilised. Responses which are “Below Threshold” have much room for further improvement in their lean application and shared mental models development to reduce the occurrence of construction wastes and lower the total manpower effort. All that said, the total man-days utilised can be optimised if greater attention is paid to identify areas which can greatly reduce the occurrence of construction wastes rather than focusing on the reduction of manpower effort (Liker 2004).

7.6 Modelling 7.6.1 Neural Network Structure The neural network was generated based on the information as shown in Table 7.12. The neural network diagram derived is shown in Fig. 7.8 and the respective synaptic weights are shown in Table 7.13. Table 7.14 displays the results of training and applying the network to the sample. The percentage of incorrect predictions of the leading indicator of precast productivity performance are fairly constant across the training (21.5.%) and testing (22.2%) samples. This substantiates that the model is not over-trained and that the incorrect predictions in subsequent new cases to be added to the model will be close to the percentage reported in this table.

128

7 Results and Analysis

Table 7.12 Neural network information Sample

Training

79

68.7%

Testing

36

31.3%

Valid

115

100.0%

Excluded

0

Total

115

Input layer

Covariates

Hidden layer(s)

Output layer

a Excluding

LP1–LP14 and SMM1–SMM10

Number of unitsa

24

Rescaling method for covariates

Standardized

Number of hidden layers

1

Number of units in hidden layer 1a

2

Activation function

Hyperbolic tangent

Dependent variables

1

Leading indicator of precast productivity performance

Number of units

2

Activation function

Hyperbolic tangent (for classification between two classes)

Error function

Cross-entropy

the bias unit

7.6.2 Independent Variable Importance Analysis Table 7.15 shows that both the lean construction principles and shared mental models have an effect on how the network classifies the leading indicator of precast productivity performance. To reduce construction wastes, it is important that team members make decisions that will make sense in the long run rather than in terms of short-term gains which is the foundation of lean construction principles. Team members should also be equipped with adequate skillset and are assigned tasks that matches with their capability. This is because individuals have to perform the actual detailed work and teams have to coordinate the work and learn from each other. This balance between individuals and teamwork is critical so that team members can gain a complete understanding of the precast construction process as they strive to reduce construction wastes through lean implementation and improve productivity. The importance of developing shared mental models is established in the study by Goodwin et al. (2008) who suggested that shared mental models attributes are significant predictors of problem-solving outcomes. The development of shared mental model as a precondition should not be underestimated. According to Cassidy and Stanley (2018), shared mental models have an important effect of providing team members with better communication links to converge as they continue to execute

7.6 Modelling

Fig. 7.8 Multi-layer perceptron network structure

129

130

7 Results and Analysis

Table 7.13 Synaptic weights of respective parameter estimates Predictor

Predicted Hidden layer 1

Input layer

Hidden layer 1

Output layer

H(1:1)

H(1:2)

Below threshold

Above threshold

(Bias)

0.225

0.859

LP1

0.663

−0.231

LP2

−0.284

0.016

LP3

−0.403

0.114

LP4

0.676

−0.458

LP5

0.421

0.102

LP6

−0.379

0.403

LP7

−0.318

−0.16

LP8

−0.27

0.489

LP9

−0.213

−0.056

LP10

0.199

−0.114

LP11

0.574

0.604

LP12

−0.186

0.134

LP13

−0.317

−0.498

LP14

0.021

1.207

SMM1

0.499

−0.673

SMM2

−0.024

0.386

SMM3

0.491

−0.146

SMM4

−0.259

0.305

SMM5

0.7

0.014

SMM6

−0.384

0.444

SMM7

0.338

0.777

SMM8

−0.266

0.068

SMM9

−0.116

0.236

(Bias)

SMM10

0.899

−0.109 0.672

−0.595

H(1:1)

−1.017

0.423

H(1:2)

−0.772

1.255

their daily tasks. They can encode and decode their internal ideas into a shared language and coordinate their efforts with another team member to result in the intended outcome. It is required for team members to share and develop their mental models to possess the specific knowledge they need to function together effectively in the implementation of lean construction principles. Therefore, this implies that team members involved in precast construction projects are required to collaborate

7.6 Modelling

131

Table 7.14 Neural network model summary Training

Testing a Error

Cross entropy error

33.536

Percent incorrect predictions

21.5%

Stopping rule used

1 consecutive step(s) with no decrease in errora

Training time

0:00:00.02

Cross entropy error

18.507

Percent incorrect predictions

22.2%

computations are based on the testing sample

Table 7.15 Independent variable importance analysis Independent variable

Importance

Normalised importance (%)

LP14

0.11

100.00

SMM7

0.093

85.00

LP11

0.089

81.30

LP13

0.067

61.20

SMM10

0.065

58.80

SMM1

0.056

51.10

SMM5

0.045

41.10

LP4

0.042

38.50

SMM6

0.042

38.10

LP5

0.04

36.10

LP8

0.039

35.60

LP1

0.036

32.80

SMM3

0.033

29.90

SMM2

0.032

28.80

LP6

0.032

28.70

LP7

0.03

27.20

SMM4

0.028

25.30

LP3

0.024

21.50

SMM9

0.023

20.90

LP2

0.018

16.00

LP9

0.017

15.10

LP12

0.014

12.70

SMM8

0.014

12.70

LP10

0.012

10.90

132

7 Results and Analysis

in reducing the occurrence of construction wastes and build shared mental models that is central to achieving better productivity performance.

7.6.3 Classification Results Table 7.16 shows the classification results of using the neural network. For each case, the predicted response is correct if that case is predicted pseudo-probability greater than 0.50. The combined results of the training and testing samples is displayed at the boxplot in Fig. 7.9. It appears that the network does a reasonably good job of predicting the leading indicator of precast productivity performance. As evident from the testing sample, predictions for observed “Below Threshold” and observed “Above Threshold” have about the same probability of overestimating and underestimating the actual productivity performance. For overestimation, it could be because team members could be complacent and think that they have maximised their productivity performance and hence it is likely that these cases are team members who have not maximised their lean construction implementation and development of shared mental models. In this study, underestimation is better than overestimation as the key is to identify those that are “Below Threshold” and assess what improvements are required to better their productivity performance. The leftmost boxplot in blue shows, for cases that have observed category “Below Threshold”, the predicted pseudo-probability of category “Below Threshold”. The portion of the boxplot above the 0.5 mark on the y axis represents correct predictions shown in the Table 7.16. The portion below the 0.5 mark represents incorrect predictions. The second boxplot in green to the right shows, for cases that have observed category “Above Threshold”, the predicted pseudo-probability of category “Above Threshold”. It is noted that the network predicts a substantial number of cases in both the “Below Threshold” and “Above Threshold” categories using the 0.5 cut-off, so only minor portion of the box is misclassified. If the cut-off is lowered from 0.5 to 0.3, the chances of correctly predicting “Below Threshold” increases but the chances of Table 7.16 Classification results of using the neural network Sample

Observed

Predicted Below threshold

Above threshold

Training

Below threshold

35

10*

Above threshold

7*

27

79.4

Overall percent

58.3%

41.7%

78.5

Below threshold

14

3*

82.4

Above threshold

5*

14

73.7

Overall percent

52.8%

47.2%

77.8

Testing

*Wrongly predicted

Percent correct (%) 77.8

7.6 Modelling

133

Fig. 7.9 Predicted by observed boxplot

wrongly predicting “Above Threshold” increases. There should be a balance between the correct predictions for each of the two categories and hence, the single cut-off at 0.5 shall remain. Furthermore, the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curves for this neural network model is 0.861 as shown in Fig. 7.10. Specificity versus sensitivity chart to show the probability of being tested true positive with a positive test result versus the probability of being tested true negative with a negative test result. According to Fawcett (2006), AUC score above 0.5 is a good indicator of a sound classification performance. This means that the probability that this model is able to distinguish a randomly chosen positive samples from a randomly chosen negative samples is 86.1%. Cumulative gains chart to show the percentage of the overall number of cases in each category (i.e. Below Threshold or Above Threshold) gained by targeting a percentage of the total number of cases. In addition, the cumulative gains chart shown in Fig. 7.11 indicate the percentage of the overall number of cases in each category, that is, Below Threshold or Above Threshold, gained by targeting a percentage of the total number of cases. For example, the blue curve for the “Below Threshold” category shows that the top 30% of cases is expected to contain approximately 55% of “Below Threshold” cases. The gap

134

7 Results and Analysis

Fig. 7.10 Specificity versus sensitivity chart

between the blue or green curves and the baseline indicates the gains that was observed from using the predictive model to determine the leading indicator of precast productivity performance. The lift chart is derived from the cumulative gains chart and the values on the y axis correspond to the ratio of the cumulative gain for each curve to the baseline as shown in Fig. 7.12. Hence, the lift at 30% for the “Below Threshold” category is 55%/30% = 1.83. This means that it is 1.83 times more likely that the leading indicator of precast productivity performance can be predicted by using this model than if there was no model. Based on the above measure of the effectiveness, the neural network prediction model that was trained to predict the leading indicator of precast productivity performance, using the reduction of construction wastes due to lean principles and shared mental models development, is assessed to perform reasonably well. The 24 attributes resulting in the reduction of construction wastes due to the lean principles and shared mental models development as well as the 11 attributes resulting in the reduction in the total-days utilised could serve as a project management plan for the contractor to evaluate how things are being done at present. These will then be fed into the prediction model to determine if the potential precast productivity performance will be “Above Threshold” or “Below Threshold”.

7.7 Summary

135

Fig. 7.11 Cumulative gains chart

7.7 Summary With the increasing demands of construction projects, coupled with the lack of resources and experienced personnel, it is challenging for contractors to determine how well they are doing and proactively intervene to improve productivity. The precast productivity performance leading indicator can potentially be used to guide contractors to identify areas that have not been done well so that the necessary measures can be taken before actual implementation. This will ensure that the eventual productivity performance of precast construction projects will be much better than if such benchmarking was not done. Without measuring something, it is impossible to improve it and this means that one needs to determine the construction wastes and measure its effect on the total man-day utilised during the entire precast construction process. In order to understand the unnecessary processes to be eliminated throughout the precast construction stages, the relationships of team members’ mental models must be reasoned so that they can interpret, structure the environment and communicate the tasks to be done. In particular, the added effect of developing shared mental models among the team members is shown to further reduce the occurrence of construction

136

7 Results and Analysis

Fig. 7.12 Lift chart

wastes and result in better productivity performance. For projects which are “Below Threshold”, this study have brought attention that their current mental model is not coherent for precast construction projects and explained how they can develop a new shared mental model to engender the spirit of lean principles effectively. Besides learning the technical aspects of precast construction, contractors need to take a step back and explore how they should internalise the new experience of managing precast construction projects and strengthen or adjust their shared mental models to achieve better performance. The construction industry is still working to develop their shared mental models among the team members as seen through collaborative frameworks such as ECI, integrated project delivery and BIM being strongly advocated. Shared mental model needs to work hand-in-hand with lean principles to result in successful implementation of the contractor’s precast construction capability at the enterprise level. Hence, the contribution of enabling lean in precast construction through developing shared mental models should not be neglected to achieve higher precast productivity performance. Table 7.17 summarises the insights on the effects of development of the team’s shared mental models in the reduction of construction wastes with the implementation

Design approvals

Mr. B—“We will submit the shop drawings and get the consultant to check…sometimes, we had to ask the precaster to proceed even before obtaining the consultant’s approval. This have caused some reworks downstream due to changes to the design”

Mr. C—“…our draftsmen will do up the shop drawings, then our engineers will check to ensure compliance with the consultants drawings. If this process is not in place, we would have big problem during production…” Mr. D—“For example, items in which there is no repetition, we will plan for it to be done cast in-situ. The more times the moulds are being re-used, the lesser man-days would be required” Mr. F—“After the mould have been reused many times, it may run a little and the dimensions will be out. We have critical points in place to identify these and will make the improvements immediately to ensure the quality of the next element being produced”

Standardisation, Simplification and Single Integrated Elements

Interfacing Coordination and Connection; Alignment and Construction Tolerance

Mr. B—“We will also bring in the precaster during tendering stage to look into the possibility of further standardising the design” Mr. D—“One suggestion is that buildability and constructability should be considered by all parties even during the URA Planning Permission stage as changes downstream would be counter-productive”

Key interview findings

Early Contractor Involvement; Accessibility for Assembly

Design stage

Precast construction considerations

Lean efforts are needed to establish an integrated platform for the whole process of precast construction and facilitate the cooperation among stakeholders. This promotes greater clarity, accuracy, and timeliness

This strongly resonates with the lean principle that standardising tasks are the foundation for continuous improvement and employee empowerment. Using modularised and prefabricated components can help to overcome the common production problems encountered during on-site construction such as low output quality, low productivity, high variability, and poor safety. Employees should also be able to identify tasks in which there is no value to standardise and work together to coordinate and integrate both the standardised and non-standardised tasks into the entire process This also strongly resonates with the lean principle of building a culture of stopping to fix problems to get quality right the first time. Having a systematic approach to identify failures, develop, implement and evaluate the effectiveness of the potential solutions before continuing the process is key to prevent construction wastes from escalating

This strongly resonates with the lean principle to grow together with solid subcontractors and suppliers. The main contractor, precaster, subcontractors and suppliers must all work collaboratively upfront to ensure that the project can be delivered productively. Consultants’ inputs should also be sought right from the start to result in an optimum design with stretched value to facilitate the downstream processes

Key lean enablers

Table 7.17 Lean enablers reinforcing shared mental models in precast construction

(continued)

The shared mental models construct requires individuals to have a sense of being in common and communicate effectively. If there are any issues holding up the progress, individuals should take the initiative to understand the situation and work as a team to resolve them

The shared mental models theory suggests that team members should integrate the various knowledge in their respective roles so that adversarial practices and disjointed processes can be avoided. Furthermore, the development of shared mental models helps to foster convergence at key milestones and allow team members to close knowledge gaps and work through any issues

Having shared mental models among team members allows them to adjust their strategies quickly and efficiently. This is critical in the process of organisational change which is the shift from on-site construction to off-site construction in this case

Reinforcing shared mental models

7.7 Summary 137

Mr. A—“We need to have a strong drafting team, able to foresee downstream problems during production and connection issues. Once the shop drawings are not correct, there would be rework at the precast yard and even on-site” Mr. D—“Project managers who are very experienced and capable would be able to foresee problems and make effort to bring everybody together and remove wastes”

Human resource management

Protection; Transportation; Lifting

Mr. A—“In Singapore, most of the sites are very tight and there is no space or holding area for storage of the precast components. We have to work with the contractor on the schedule and do just-in-time delivery. This is very challenging due to traffic jams and custom clearance. Sometimes, the driver had to wait hours outside the site due to site coordination issues and they are not ready to unload and install. Our driver can only go back to Malaysia after they have unloaded”

Mr. C—“…the client’s appointed RTO are also stationed at the precast yard to do quality inspections” Mr. E—“…there would be a cascading effect if the team do not work well together and not passed down the required information promptly…”

Total Quality Management

Logistics stage

Mr. B—“…precaster typically prefers to complete the casting for all same type of components at one go for efficiency. If this is the case, the precaster would have to have a holding area at their precast yard to store these precast components first as the site would not have space for early delivery of these items” Mr. C—“Sometimes, for large precast components, the contractor will do casting at the on-site yard as there are challenges to transport the huge precast item and is riskier. They will weigh the pros and cons, whether there is space on-site and whether it is cost effective as they will need to incur cost to set-up the on-site yard but will save on logistics cost”

Key interview findings

Factory Location and Capacity; Plant and Machinery Capabilities

Production stage

Precast construction considerations

Table 7.17 (continued)

This strongly resonates with the lean principle to maintain a continuous material flow that matches the requirements to optimise inventory and work-in-progress. To do so, a reliable information of the progress on-site and demand forecast are required to plan the ideal quantities to be catered in each lot

The lean model believes in having close alignment and coordination within the entire precast construction process through partnering and transparency in information flow. There needs to be a continuous workflow with the repetition of tasks in precast construction which allows deviations to be recognised early so that improvement measures can be implemented on time

Key lean enablers

(continued)

Having shared mental models facilitates consistent task execution, which leads to higher commitment to organisational change in novel and ambiguous contexts. A shared mental model among the team members can also assist them to build team norms and consensus, which then enhances support to tackle any unexpected situations. This allows changes to be make quickly, confining the negative impacts to the smallest extent

The shared mental models theory suggests that effective communication is required at all levels to drive forward an agenda for improvement. This will ensure that all team members are aware of the on-going problems and stop performing the wrong steps immediately. In addition, leaders should share personal knowledge to train team members who are responsible for the actual tasks delivery

Reinforcing shared mental models

138 7 Results and Analysis

Mr. E—“…practicing lean, doing value stream mapping right from the design stage to remove wastes. Every project would need to re-think and customised its own value stream mapping based on the design, complexity, size, etc.”

Mr. D—“The adoption of BIM will also help. I think contractors should have their own BIM coordinator on-board the project to investigate such issues. Relying on the BIM manager from the consultants is not as effective because consultants themselves typically focus on compliance issues and would not be able to think about constructability problems downstream” Mr. E—“…depending on the resources allocated to the project by the company…the project manager will then be able to get his people to take time…picking up such new technologies and lean approaches…”

Mr. A—“Depending on the complexity of project, we do send our engineers to our factory in Malaysia to inspect the production, ensure that things are done correctly and quality is up to standard” Mr. B—“…we send our own staffs over to do periodic inspection to ensure the quality”

Building Information Modelling and Virtual Design and Construction; Info-Communications Technology

Critical Inspections and Quality Checks

Key interview findings

Construction and Project Management

Installation stage

Precast construction considerations

Table 7.17 (continued)

Lean is about enabling quality at source, having procedures to detect when an abnormal condition has occurred and immediately stop work to resolve the problem

Management support is important to connect people with these technologies to facilitate information for a more accurate and efficient precast construction process

Lean construction is about institutionalising a planning and control framework to remove construction wastes at each preceding construction work trades

Key lean enablers

By developing shared mental models, team members are better equipped to anticipate unforeseen circumstances, and seamlessly coordinate to develop common, unspoken schemas to work out the problematic tasks

Commitment is crucial during technological implementation to achieve better performance. People must be competent and available to drive the implementation process by working as highly coordinated units

The shared mental models theory suggests that transferring and sharing tacit knowledge is a critical task for people involved in precast construction. There needs to be greater understanding of the how-to approach and the factors that drive the success of transferring and sharing tacit knowledge to minimise construction wastes

Reinforcing shared mental models

7.7 Summary 139

140

7 Results and Analysis

of lean construction principles to deliver a precast construction project which is “Above Threshold”. It shows that the reduction of the occurrence of construction wastes and man-days utilised do not happen by chance but it is also influenced by the dynamics of the team involved in the precast construction project in terms of their task knowledge and team knowledge. This refers to the team structure, strategies, information sharing, coordination efforts and understanding of their own task as well as their team members’ task which will have an impact on the leading indicator of precast productivity performance. It is noted that the forecast should not be interpreted as an absolute prediction and experienced personnel’s judgement should also be considered when evaluating the projects. Thus, even if a project is forecasted to be “Above Threshold”, contractors should exercise careful judgement on whether there are still room for further improvement in their precast productivity performance which is at the core of kaizen to creating a culture of continuous improvement.

Chapter 8

Case Study

8.1 Overview This chapter aims to prove that inputs of the neural network model generated was effective to allow contractors to predict the risk of low construction productivity at an early stage of the precast construction process and enable them to proactively take actions to further optimise the total man-days to be utilised in the subsequent precast construction stages. This was done through validating the neural network model in two projects by assessing the changes in the occurrence of construction wastes and see whether the model correctly classifies their precast productivity performance into the correct category—“Below Threshold” or “Above Threshold” based on the observed changes in the total manpower usage. As part of the validation process, the performance of the neural network was also evaluated by determining the number of correct predictions against the actual number in the specific category to confirm its predictive ability. It was found that the model inputs allowed contractors to forecast their precast productivity levels and identify areas that they should focus on to further reduce the occurrence of construction wastes and consequently optimise the total man-day required throughout all the precast construction stages, both on-site and off-site.

8.2 Background This section analyses two local industrial precast projects by the same main contractor to investigate the impact of enabling lean and having shared mental models development on the occurrence of construction wastes and the total man-days, both on-site and off-site, used throughout the precast construction process. Table 8.1 shows the background of the precast construction projects. Due to the sensitivity of the information, project-specific details collected which are able to © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_8

141

142

8 Case Study

Table 8.1 Background of projects Project No.

1

2

Project duration (months)

14

18

Constructed floor area (m2 )

4198

6498

Project productivity (m2 per man-day)

0.614

0.625

Site management team (man-day)—not included in project productivity calculation as only on-site workers are considered

910

1382

Basement (man-day)





Structure works (man-day)

1770

2687

Architectural works (man-day)

1322

2009

Building services and M&E works (man-day)

2946

4478

General (man-day)

379

576

External Works (man-day)

418

640

reveal the actual projects could not be included in this study. As it is recognised that the varying factors such as building design, site constraints, scope of works, mechanisation and management tools adopted would affect the analysis and discussion, two projects of similar complexity and size were chosen. The boundary of this case study for the research validation shall be primarily based on the factors listed in Table 8.1 to allow for an objective and meaningful comparison. The mixed-methods approach was utilised to gain a deeper understanding of the two projects by comparing the survey responses with the quantitative productivity monitoring data obtained as well as qualitative interviews to further validate the 24 inputs of the neural network model. Qualitative data were collected via an interview session with the Director from the main contractor as summarised in Appendix K and quantitative data were collected from the survey responses. Although the precaster involved in these two projects was not interviewed, it is deemed that this have no adverse impact to the neural network validation. This is because the analysis of variance (Sect. 7.3) from the survey responses have shown that there is no statistically significant difference in the views among the five team members from the main contractor and precaster. Moreover, based on the inputs gathered from the six post-survey interviews to validate the survey findings, it was shown that the three main contractors were also able to share inputs during the production and logistics stages which the precaster is directly involved in. This is due to the fact that main contractors manage the entire precast construction process and their requirements will guide the work of the precaster. Similarly, the three precasters were also able to share inputs that should be taken care of during the respective stages of the precast construction process. The work activities of the precaster and main contractor are interdependent on each other and both of them need to know what is going on, whether it is design changes or transportation issues, etc. so that they can work together to minimise construction wastes and man-effort by adjusting the work activities accordingly.

8.3 Findings

143

8.3 Findings Using the neural network modelled in Chapter Seven, the survey responses of these two projects were partitioned with each being validated separately and the results are shown in Table 8.2. The model accuracy at 82.9 and 72.6% shows that the model prediction is very close to the actual dataset and the training data indicates a good fit. Next, one out of five main approaches was used to evaluate the model performance as the approach chosen depends on the interest of this study. They are Accuracy, Kappa, Weighted-Kappa (Kw) Statistics, Recall and Precision as illustrated in the equations below. Accuracy (Eq. 8.1) can be used to evaluate the overall model performance but it does not consider the type of prediction errors being made. Kappa (Eq. 8.2) only measures the strength of agreement and does not consider the effect of disagreement. Kw (Eq. 8.3) can account for the type of prediction error being made, measure the magnitude of agreement and impose penalties on errors that are further away from the true results between the collected data and the predicted data. Since there are only two classes in this study, the Kw Statistics would be equal to Kappa. Accuracy =

Corr ect Pr edictions Corr ect Pr edictions + W r ong Pr edictions

(8.1)

Table 8.2 Comparison of classification results Model

Sample

Project No. 1 validation (4 out of 5 team members responded)

Project No. 2 validation (2 out of 5 team members responded)

* Wrongly

Training (111)

Validation (4)

Training (113)

Validation (2)

predicted

Observed

Predicted Below threshold

Above threshold

Percent correct/accuracy (%)

Below threshold

51

7*

82.9%

Above threshold

12*

41

Below threshold

4

0

Above threshold

0

0

Below threshold

43

17*

Above threshold

14*

39

Below threshold

2

0

Above threshold

0

0

100

72.6

100

144

8 Case Study

K =

obser ved pr opor tion − ex pected pr opor tion o f agr eement 1 − ex pected pr opor tion o f agr eement

(8.2)

 (weights o f disagr eement level × obser ved pr opor tion in the speci f ic class) Kw = 1 −  (weights o f disagr eement level × ex pected pr opor tion in the speci f ic class)

(8.3) In the context of precast productivity performance, the implication of overlooking a “Below Threshold” (false negative) is much more serious than incorrect prediction of a “Above Threshold” (false positive). Thus, Recall (Eq. 8.4) is a suitable measure to evaluate the model performance because it takes false negative into account which Precision (Eq. 8.5) does not for each class. Based on the trained neural network model in Chapter Seven, for both the “Below Threshold” and “Above Threshold” in this model, the recall is around 0.8 which means that there is a 20% chance of overlooking an observed “Below Threshold” and “Above Threshold”. Hence, the neural network model is deemed to have substantial predictive abilities and the model performance is expected to improve if more data points are used. corr ect pr edictions in the speci f ic class actual number in the speci f ic class

(8.4)

corr ect pr edictions in the speci f ic class corr ect and wr ong pr edictions in the speci f ic class

(8.5)

Recall = Pr ecision =

8.4 Discussion The following points were gathered from the interview session on 13 out of 24 inputs of the neural network model highlighted to be significant in reducing the occurrence of construction wastes to streamline the total man-days utilised; and would have resulted in the neural network model classifying these two projects under low risk of low precast productivity performance, that is “Above Threshold”, instead of high risk under “Below Threshold”. The interviewee (Mr. G) mentioned that “our experience or issues encountered in these two projects are similar which is typical for most of our precast construction projects”. Hence, no differentiation between these two projects could be discussed. During the production stage, the fabrication schedule of the respective precast elements was not followed by the workers due to miscommunication and oversight among the team members. If the supervisor picked up this issue before delivery to the construction site, inventory would have been incurred by the precaster. If this issue was only discovered upon delivery to the construction site, the main contractor would usually find some space to store these precast items which are not required yet or ask the precaster to bring back these precast items till it is ready to be received at site as per the agreed schedule. In both projects, the sequence of doing things had to be changed at the last minute in order to minimise the effort required to catch up with

8.4 Discussion

145

the schedule to produce the precast components and deliver them to site. This shows the lack of implementation of “LP7—use visual control throughout the process so no problems are hidden” and “SMM7—team members collaborate and work closely through a structured means of communication”. There were also situations where the precasters could not deliver the precast components to the construction site as there were delay in the project activities and the site was not ready to receive these precast components. As precasters are not just serving one particular project but also other projects, they have to weigh the pros and cons, prioritise and plan towards the expected schedule of all projects as per “SMM4—team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them”. The factory manufactured different types of precast components for various projects based on the demand required across all their clients’ or main contractors’ construction site. As such, the production process and speed had to be amended and downtime with starts and stops in the production line was observed. This shows the lack of implementation of “LP3—use pull systems to avoid overproduction”. During the logistics stage, there were situations where the precasters encountered traffic jams and prolonged custom clearance. This resulted in occasional idle time at the construction site while waiting for the precast components to arrive. As the workers were already on-site and they are typically trade-specific and under the charge of the subcontractor who was engaged for the specific type of work for a specific period of time, the workers could not be transferred to do other tasks. This shows the lack of implementation of “LP8—adapt operations to suit technology, people and processes”. In addition, there were changes in the design due to clashes between the structural components and M&E services. As some of the precast components based on the old design have been fabricated, there was significant rework. If the main contractor had developed a coordination process and identified such problems at the earliest opportunity, the occurrence of construction wastes could have been avoided and the total manpower usage would have been lowered. To do so, building an intensive collaborative team upfront and empowering team members to follow through the entire precast construction process were gathered to be key. There needs to be a shared intention of sustaining collaborative team practice throughout the entire precast construction process so as to accelerate knowledge building of the tasks and shared mental models in the team to reach the desired productivity performance outcome. This shows the lack of applying “SMM6—team members have a common goal and form compatible expectations to act accordingly”. It is noted that precast works are executed at the early stage of the entire construction project and team members would still have been in the process of developing the initial standardised work to be used, worked out the basic operational procedures and tested standard operating procedures. Hence, it is essential for the main contractor to cater some float time at the beginning stage so that team members can get the job duties and responsibilities right. Otherwise, they may rush and overlook on certain aspects resulting in downstream problems. During the beginning stage,

146

8 Case Study

team members should acquire a shared mental model through learning and experience to not just manage the tasks but also to promote the lean culture and teach others to go through a similar training regimen, to effect “LP10—develop your people”. After team members standardised and stabilised the work process for the initial phase as per “LP6—standardise tasks as foundation for continuous improvement”, several sprints should be conducted to see how to continuously improve the standardised work to complete the subsequent phases. As per “SMM5—team members integrate information and determine the consequences”, this is important because many different disciplines with many people making detailed engineering decisions that must fit together at the right time have to be coordinated to deliver the precast construction project. This continuous improvement process as per “LP14—review processes for continuous improvement” helps the workers to control their own work and ramp up for subsequent repetitive tasks. Besides conducting quality checks during key milestones to keep workers on their toes, the contractors must know how to get to the root cause of any problems they observe and communicate it effectively to the consultants and/or subcontractors. However, contractors and consultants did not personally go and see for themselves and rely on the resident engineer or resident technical officer to supervise and update them via emails. As such, many observations cannot be seen from written reports, photographs and numbers as they do not reveal the details of the actual tasks being done. This may have resulted in more construction wastes and is not a good practice as the quality management process should have been tightened and strictly adhered to. This shows the importance of “LP12—go and see for yourself to thoroughly understand the situation”. It is key to have on-site observations at the factory and construction site, as well as frequent communication with the respective site personnel. It is also about a judgement on the management of the workers and empowered individuals to contribute to the elimination of construction wastes and influencing the impact of precast productivity performance. Team members should have a sufficient level of understanding about what tasks other individuals in the team are performing as per “SMM9—crosstraining to equip team members with a shared knowledge of their teammates’ work”, knowing enough to allow for effective communication such that critical information can be transmitted to the rest of the team promptly as per “SMM3—team members share information that is previously possessed individually by each team member to others in the team”. With that, they would be able to address issues as these arise and appropriately communicate them to navigate difficult scenarios. This implies that a major determinant of the leading indicator of productivity performance was about the team dynamics and not just the experience level of the team members. This case study showed that with improvements in the further implementation of the abovementioned 13 attributes to reduce the occurrence of construction wastes to streamline the total number of man-days, the neural network model would have classified these two projects under low risk of poor precast productivity performance, that is “Above Threshold”. It is noted that these 13 attributes gathered to be significant to result in an enhanced precast construction capability in this case study are not the same top 13 attributes gathered from the independent variable importance analysis

8.4 Discussion

147

in Sect. 7.6.2 which is expected given that the level of lean construction and shared mental models implementation varies among the contractors. Moreover, every project is different and would result in different extent of the reduction in construction wastes and total manpower used.

8.5 Validation An interesting point to note is that the on-site productivity figures for both projects in m2 per man-day at around 0.6 are relatively high as compared to the industry’s average at 0.554 based on the industrial building category in Year 2017 when both projects were completed. However, the neural network model categorised both projects under “Below Threshold” which shows that more could be done to further reduce the construction wastes and optimise the manpower usage. The actual project productivity figure is more optimistic as it only accounts for on-site man-day. If the off-site man-day were also considered as discussed above, productivity issues which occurred during production at the factory and logistics handling would have lowered the overall precast productivity performance. The interviewee (Mr. G) also supported that both projects being classified under “Below Threshold” was expected as construction wastes which could be avoided were still observed. To ensure an apple-to-apple comparison considering both on-site and off-site manpower, this case study would simulate the off-site productivity figures which would be added to the on-site productivity figures obtained from the contractor. This is to truly validate the neural network model’s ability to classify Project No. 1 and 2 into the correct category, that is, “Below Threshold” based on empirical data, inputs from BCA, the main contractor and third-party experts’ judgment of off-site productivity figures. After consultations with BCA, the main contractor was asked to estimate the off-site man-day based on their understanding of both projects. Thereafter, Mr. A and Mr. B were asked to provide their views on the estimation done. A sensitivity analysis was then performed to validate the estimation done. The validation approach and sensitivity analysis are shown in Table 8.3. The results of the validation are shown in Table 8.4 (for Project No. 1) and Table 8.5 (for Project No. 2). These tables highlight the on-site and simulated off-site productivity for both projects. The results demonstrated that the neural network model can reliably predict the leading indicator of precast productivity performance for both projects.

8.6 Conclusion As a whole, all 24 attributes should still work hand-in-hand to methodically bring about precast construction capability development among the team members. Figure 8.1 summarises key features of the entire study model to give an overall

2687 × 1.1 = 2956

1770 × 1.1 = 1947

Simulated on-site and off-site structure works (man-day)

4

6498 m2

3

4198 m2

Constructed floor area

2

Project No. 2 0.625 10,390

On-site man-day

1

6835

Project No. 1

0.614

Data

m2 per on-site man-day

S/N

Table 8.3 Validation approach and sensitivity analysis Source and concurrence by main contractor (Mr. G)

Experts’ judgement N.A

On-site man-day was obtained from the main contractor as shown in Table 8.1 and the off-site man-day was added based on the continuum of prefabrication and DfMA which stated that adoption of structural precast elements would lead to up to 10% manpower savings (BCA 2017f). BCA clarified that the project level manpower savings mentioned in BCA (2017f) is computed by using the total on-site man-days used at project level (including architectural, M&E works and others) as the denominator. To be precise, the structural trade level manpower savings could be up to 25% for installing precast components compared to carrying out cast in-situ. On-site manpower is reduced because work activities have been transferred to the factory for activities such as preparation of formwork, steel reinforcement meshes and concrete casting The main contractor concurred that standard precast elements were used in both projects and that it could be estimated that about 10% off-site man-day was incurred for activities in the factory and transportation to site. If traditional cast in-situ construction was adopted, the total man-days utilised should be slightly more. Although higher number of on-site workers are required for activities such as formwork and safety due to working-at-height, off-site workers are not required during the logistics process for activities such as loading and unloading of precast elements

Obtained from the main contractor as shown in Table 8.1

(continued)

Mr. A is of the view that the off-site man-day estimated could be slightly lower than the 25% trade level figure as works were done in a factory-controlled environment which makes things easier to manage and minimisation of construction wastes can be better implemented. The 10% used seems to be on the low side but only the parties involved would be able to give an accurate figure Mr. B is of the view that the off-site man-day estimated depends on the number of components which are precast, that is, slab, beam and/or column which varies from project to project, ranging from 0 to 25%. It could be more than the 10% used. The stakeholders involved should be able to provide a better estimation as they have full information of the project details

N.A

Obtained from the main contractor as shown in Table 8.1 N.A and hence, this figure should have already taken into consideration the on-site man-day utilised due to enabling lean through using shared mental models in both projects as responded in the survey

Obtained from the main contractor as shown in Table 8.1

148 8 Case Study

Data

Simulated on-site and off-site architectural works (man-day)

S/N

5

Table 8.3 (continued) Project No. 2 2009 × 1.3 = 2612

Project No. 1

1322 × 1.3 = 1719

Source and concurrence by main contractor (Mr. G) On-site man-day was obtained from the main contractor as shown in Table 8.1 and the off-site man-day was added based on the continuum of prefabrication and DfMA which stated that adoption of on-site dry applied finishes would lead to up to 30% manpower savings (BCA 2017f). BCA clarified that the 30% savings for on-site dry applied finishes is due to removing the need for in-situ finishes, which usually comprises three steps—plastering, primer coat and base coat The main contractor concurred that dry construction such as prefabricated internal wall panel with on-site dry applied finishes were used in both projects and that it could be estimated that 30% off-site man-day was incurred for activities in the factory and transportation to site. This percentage is much more than structural works as higher level of precision is required for architectural works to achieve consistent and good workmanship quality which now takes place in the factory instead of on-site (e.g. using cast in-situ concrete walls and brickworks) and hence, there should not be much difference in the total man-days utilised

Experts’ judgement

(continued)

Mr. A is of the view that the off-site man-day estimated could be about there or slightly lower, depending on how works are being managed on-site as well as weather conditions which may deter on-site works from continuing resulting in construction wastes such as waiting time and reworks Mr. B is of the view that the off-site man-day estimated depends on the amount of dry system being used. If wet method requires 100 man-days in total, dry method would definitely be lower than 100 man-days as finishing materials are fabricated by machine. The 0–30% range is there because the amount of dry and wet method adoption varies from project to project. Again, the stakeholders involved should be able to provide a better estimation as they have full information of the project details

8.6 Conclusion 149

Data

Simulated on-site and off-site building services and M&E works (man-day)

S/N

6

Table 8.3 (continued) Project No. 2 4478 × 1.15 = 5150

Project No. 1

2946 × 1.15 = 3388

Source and concurrence by main contractor (Mr. G) On-site man-day was obtained from the main contractor as shown in Table 8.1 and the off-site man-day was added based on the continuum of prefabrication and DfMA which stated that adoption of flexible water pipes and prefabricated pre-insulated ducting would lead to up to 30% manpower savings (BCA 2017f). BCA clarified that the 30% manpower savings is due to lesser in-situ joints required versus traditional copper piping and/or fixed sprinkler brackets However, only 15% off-site man-day was added for activities in the factory as the main contractor estimated that about half of the manpower savings was attributed to the easier on-site installation due to adoption of more buildable M&E features

Experts’ judgement

(continued)

Mr. A deemed that the off-site man-day estimated is reasonable since this project should not have much M&E works and did not adopt prefabricated MEP modules. There are industrial projects which have significant portion of M&E works such as air-conditioning as the equipment that are required to be stored needs to be maintained at a certain temperature and humidity. If prefabricated MEP modules were adopted, the off-site man-day could be much higher than the 15% estimated here though there should be slight reduction in the total man-day utilisation compared to doing all the activities on-site. This is because works are done in a safer and factory-controlled environment and hence, workers tend to be more productive Similarly, Mr. B deemed that the off-site man-day estimated depends on the extent of prefabrication. The stakeholders involved should be able to provide a better estimation as they have full information of the project details

150 8 Case Study

Data

Simulated on-site and off-site general works (man-day)

Simulated on-site and off-site external works (man-day)

Simulated on-site and off-site man-days (with minimisation of construction wastes)

S/N

7

8

9

Table 8.3 (continued)

Project No. 1

7851

418 (no change)

379 (no change)

Project No. 2

11,934

640 (no change)

576 (no change)

Source and concurrence by main contractor (Mr. G)

Experts’ judgement

(continued)

Mr. A and Mr. B have no objection that off-site man-day could be taken to be negligible

Mr. A and Mr. B have no objection that off-site man-day could be taken to be negligible

Summation of S/N 4–S/N 8. This figure is estimated to N.A have taken into consideration the off-site man-day utilised due to enabling lean through using shared mental models in both projects as responded in the survey. This is because the percentages applied to derive the off-site man-day in S/N 4, 5 and 6 is based on the best-case scenario with optimisation of the manpower utilisation as concurred by the main contractor

Obtained from the main contractor as shown in Table 8.1. External works refers to works such as driveways, landscape, drainage and underground services which all must be done on-site. Hence, no off-site man-day needs to be added as concurred by the main contractor

Obtained from the main contractor as shown in Table 8.1. General works refers to works such as machine operator, quality assurance, scaffolding, safety and health which all must be done on-site. Hence, no off-site man-day needs to be added as concurred by the main contractor

8.6 Conclusion 151

Project No. 2 S/N 3 S/N 9 = 0.544

Project No. 1

S/N 3 S/N 9 = 0.535

Data

m2 per on-site and off-site man-day

S/N

10

Table 8.3 (continued) Source and concurrence by main contractor (Mr. G)

0.495×1.3 = 0.560 1.15 This approach was concurred by the main contractor with caveat that the scope of works and type of projects should be similar as other type of projects may have substantially more architectural and M&E works, for example, which may skew the figure to be added for off-site man-day. Both m2 per on-site and off-site man-day figures in Project No. 1 and 2 are below the simulated industry’s figure at 0.560. This is in alignment with the outcome of the neural network where both projects were classified under “Below Threshold” which means that both projects would be at high risk of poor construction productivity performance

BCA clarified that they have some records of off-site man-day usage but could not share them due to sensitivity. Moreover, they do not have sufficient data yet to compile and determine industry-wide productivity figures that include off-site facilities As there is no available data on the industry on-site and off-site productivity, it is suggested that this figure be calculated as follows: (a) Multiply the 2010 on-site productivity figure (i.e. 0.495) for the industrial building category by 30% as this is the benchmark that the industry is working towards to as announced by BCA in 2010 (b) Divide (a) by 1.15 to account for the off-site man-day as gathered from the mid-point of the second lower (advanced prefabricated systems) and third class (prefabricated components) of the DfMA categories as shown in BCA (2017f)’s structural project level manpower savings which is the only available published data for project level comparison. The mid-point of the second lower and third class of the DfMA categories was determined as the target as it is deemed that a slightly higher target can be set for more productive technologies to be adopted for industrial building projects

Experts’ judgement

(continued)

Mr. A deemed that this approach can only be used as a guide as the figures are unlikely to be accurate, just like the published m2 per on-site man-day figures. For example, there may be cases of workers not being accounted as they are not registered in the biometric system. This is quite common as the worker may be assigned to go to different sites on different days, depending on the work activities to be carried out and the site progress Mr. B deemed that this approach can only be used as a rough gauge as GFA cannot reflect the scope of works for the project. For example, two projects, of which one is M&E heavy and one is not, with the same GFA, will give a result that the M&E heavy project is not as productive which may not be true as the additional man-day utilised is for the M&E works

152 8 Case Study

Data

Sensitivity check based on expert’s judgement: on-site and off-site man-day

S/N

11

Table 8.3 (continued) Project No. 2 S/N 3 0.560 = 11, 604

Project No. 1

S/N 3 0.560 = 7, 496

Source and concurrence by main contractor (Mr. G)

Experts’ judgement

Overall, the experts’ judgement deemed that the off-site man-day estimated could be higher than what was simulated for structural works and lower than what was simulated for architectural works. Hence, a sensitivity check was done to determine the off-site man-day which would result in the projects being classified under “Above Threshold” For Project No. 1, the off-site man-day must be reduced by 355 (i.e. S/N 9 minus S/N 11: 7851 − 7496 = 355) from 1016 (i.e. S/N 9 minus S/N 2: 7851 − 6835 = 1016) to 661 in order to be classified under “Above Threshold” For Project No. 2, the off-site man-day must be reduced by 330 (i.e. S/N 9 minus S/N 11: 11,934 − 11,604 = 330) from 1544 (i.e. S/N 9 minus S/N 2: 11,934 − 10,390 = 1544) to 1214 in order to be classified under “Above Threshold” This shows that reduction to the off-site man-day estimated must be quite substantial in order for both projects to be classified under “Above Threshold” which is unlikely due to the following: • Mr. A estimated that the off-site man-day for structural works is only slightly lower than the 25% mentioned by BCA which means that the 10% simulated figure should be higher. If the off-site man-day estimated is increased, both projects would definitely be classified under “Below Threshold” based on this sensitivity analysis • Although Mr. B mentioned that the off-site man-day will depend on the degree of prefabrication and dry method being adopted, the main contractor has estimated the amount of off-site man-day based on his experience and involvement in the two projects. Hence, the off-site man-day estimation done can be deemed to be reliable and acceptable

8.6 Conclusion 153

154

8 Case Study

Table 8.4 Matrix of on-site and off-site man-day for Project No. 1 S/N

Data

On-site man-day (as per contractor’s electronic productivity submission system submissions)

Off-site man-day (as per simulation)

Total man-day

1

Structure works

1770

177

1947

2

Architectural works

1322

397

1719

3

Building services and M&E works

2946

442

3388

4

General works

379

Negligible

379

5

External works

418

Negligible

418

6

Total

6835

1016

7851

7

m2

8

Target

4198/7851 = 0.535

per on-site and off-site man-day

0.560

As the total on-site and off-site productivity figure at 0.535 is lower than the estimated target at 0.560, Project No. 1 is deemed to be classified under “Below Threshold” Table 8.5 Matrix of on-site and off-site man-day for Project No. 2 S/N

Data

On-site man-day (as per contractor’s electronic productivity submission system submissions)

Off-site man-day (as per simulation)

Total man-day

1

Structure works

2687

269

2956

2

Architectural works

2009

603

2612

3

Building services and M&E works

4478

672

5150

4

General works

576

Negligible

576

5

External works

640

Negligible

640

6

Total

10,390

1544

11,934

7

m2

8

Target

per on-site and off-site man-day

6498/11,934 = 0.544 0.560

As the total on-site and off-site productivity figure at 0.544 is lower than the estimated target at 0.560, Project No. 2 is deemed to be classified under “Below Threshold”

Fig. 8.1 Prediction model for leading indicator of precast productivity performance

8.6 Conclusion 155

156

8 Case Study

big picture of this study, detailing the lean construction and shared mental models attributes used for predicting the risk of poor construction productivity throughout the precast construction process. Therefore, it could be validated that the neural network model with all the lean construction attributes and shared mental models attributes allow contractors to forecast their precast productivity levels and identify areas that they should focus on to further reduce the occurrence of construction wastes and consequently optimise the total man-day required throughout all the precast construction stages, both on-site and off-site.

Chapter 9

Conclusion and Recommendations

9.1 Discussion of Main Findings An overview of the past and present state of construction productivity in Singapore have revealed the unexplored barriers holding back the optimisation of manpower usage. This research have suggested the importance of changing mind-sets across the entire construction value chain and the way people work to help the industry embrace lean construction. A holistic approach is needed that focuses not just on reducing on-site manpower with precast construction but leveraging on lean implementation to remove construction wastes to minimise the total manpower required on-site and off-site. The construction industry should be sensitive towards the elimination of unnecessary processes or construction wastes involved in precast construction and not take for granted that simply adopting precast construction will eventually result in the maximum reduction of the total man-days required. This is because precast construction is vastly different from the traditional cast in-situ construction in which a significant portion of activities now takes place in the factory and close coordination with on-site works is required. This calls for the need to have a collaborative team practice to transform the tasks knowledge into the desired team outcomes and eliminate construction wastes. With a different construction approach, it is important to also consider the off-site manpower and streamline the precast construction process to result in optimal manpower utilisation and high productivity performance. A review of the Toyota Way, describing its evolvement have shown how lean practices can best be adopted and what actions contractors should take to reduce construction wastes and the man-days required throughout the precast construction process. This research have also showcased the means to predict precast productivity risk by providing a leading indicator to facilitate proactive improvements based on enabling lean through shared mental models for the entire precast construction process.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3_9

157

158

9 Conclusion and Recommendations

The first objective identified in Chap. 1 is to investigate the state of productivity in the local construction industry with focus on the manpower situation. It was found that the construction industry is still heavily reliant on cheap and low-skilled foreign workers and construction methods are labour intensive. This is one key reason for the industry’s poor productivity, quality, and safety record. Although off-site construction have been identified to be the way to go as it is more labour-efficient and uses laboursaving technologies, the productivity improvement results are slow as not many projects are suitable to adopt the highest degree of off-site construction method. The second objective identified in Chap. 1 is to review the different levels of precast construction with understanding of the occurrence of construction wastes at each process. It was illustrated that there is a high entry barrier to adopt precast construction as there are significant process change from on-site to off-site construction with substantial amount of activities taking place in the factory. The consultants have to design the building to suit the precast construction methodology. The contractors have to deal with the additional logistics involved in precast construction as well as train their workers to adapt to the new construction workflow so as to optimise the manpower usage and reap the benefits of higher productivity. The third objective identified in Chap. 1 is to apply lean construction principles to make improvements to the respective process of precast construction which facilitates the development of precast productivity performance leading indicator. It was found that implementation of the fourteen lean construction principles is critical to minimise the occurrence of construction wastes in precast construction. Lean practices will help to optimise the entire precast construction process throughout the design, production, logistics and installation stages to result in a lower total man-day required. The fourth objective identified in Chap. 1 is to develop a model to predict the precast productivity performance leading indicator based on the extent of the occurrence of construction wastes with lean and shared mental models application. The shared mental models theory explained how team members should collaborate and work towards a common goal to complete the tasks throughout the precast construction process to result in reduction of the occurrence wastes. The lean construction principles explained the management of precast construction to remove construction wastes and lead to reduction in manpower usage during the design, production, logistics and installation stages. Hence, both the shared mental models and lean principles are leading indicators that can be used to predict the precast productivity performance throughout the entire precast construction process. The fifth objective identified in Chap. 1 is to validate the prediction model that can be used by contractors to classify the risk of low construction productivity performance at an early stage of the project. The neural network model can classify precast construction projects into either “Below Threshold” or “Above Threshold” performance. This will allow contractors to forecast their precast productivity levels and identify areas that they should focus on to further reduce the occurrence of construction wastes and consequently optimise the total man-day required throughout all the precast construction stages, both on-site and off-site. The leading indicator of precast productivity performance will help contractors to realistically reflect the

9.1 Discussion of Main Findings

159

practical aspects which are lacking so that they can put Kaizen’s cycle of continuous improvement into action for enhancing ground implementations.

9.2 Concluding the Hypotheses To sum up, it was found that all five hypotheses were supported as shown in Table 9.1. Overall, there is a need for contractors to have a long-term commitment on building up their enterprise precast construction capability so as to sustain the implementation of precast construction in Singapore to result in reduction in the occurrence of construction wastes and the total man-day utilisation.

9.3 Contributions to Knowledge and Practice Prior to this study, there was little research dedicated to lean construction in the local construction industry in terms of streamlining manpower usage for precast construction. Existing studies have either investigated lean principles for applicability to the construction industry in general or applicability in the production and logistics stages. None studied on the relationship between the occurrence of construction wastes in precast construction and lean implementation throughout the design, production, logistics and installation stages which have been addressed in this study. Although precast construction when compared with traditional cast in-situ construction can help to raise productivity, there are still opportunities to further enhance various precast construction processes that this study have addressed. Contractors are still encountering high occurrence of construction wastes and the pool of foreign workers have not reduced significantly. Studies which have researched on manpower usage for precast construction focuses on the off-site processes. None studied on the combined effects of both on-site and off-site processes to assess the effective manpower required which have been addressed in this study. Moreover, there is an apparent lack of framework or methodology to understand the derivation of manpower changes by considering lean construction throughout the precast construction process. Hence, another contribution of this study involves the use of shared mental models theory to highlight the multifaceted impact of lean principles and assess how team members can work together throughout the precast construction process to minimise construction wastes. A different approach is taken by assessing how team members involved in a precast construction project work together to minimise wastage of materials, time and effort throughout the precast construction process. The contribution lies in the results illuminating how shared mental model can shape team performance to reduce construction wastes and streamline manpower requirements. The shared mental models theory have brought out the soundness of this study as an important ubiquitous system for the numerous precast construction projects in time

Supported

The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction in the total man-days used in precast construction

The reduction of construction wastes due to the development of shared mental models would have a positive effect on the reduction in the total man-days used in precast construction

1

2

3

Supported

Supported

Status

The reduction of construction wastes due to the implementation of lean construction principles would have a positive effect on the reduction of construction wastes due to the development of shared mental models

Hypothesis

Table 9.1 Review of hypotheses

(continued)

The reduction of construction wastes due to the development of shared mental models among the team members will result in reduction in the total man-days used in precast construction. It has been explained in this study that shared mental models have an important effect of providing team members with better communication links to converge as they continue to execute the precast construction activities. With that, they can interact and coordinate their efforts with other team members to optimize the processes and reduce the total man-days utilisation

When reduction of construction wastes due to the implementation of lean construction principles is observed, there will also be reduction in the total man-days used in precast construction

When reduction of construction wastes due to the implementation of lean construction principles is observed, there will also be reduction of construction wastes due to the development of shared mental models. These 24 attributes go hand in hand to result in reduction in the occurrence of construction wastes during the entire precast construction process. Given that the four main stages of precast construction are not a pure sequential process, the many activities taking place at the same time will augment communication and coordination which will potentially increase the reduction of construction wastes in totality. The combined effect of lean principles and shared mental models need to be embraced for reflexivity

160 9 Conclusion and Recommendations

Supported

The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the development of shared mental models

4

5

Supported

Status

The leading indicator of precast productivity performance is dependent on the reduction of construction wastes due to the implementation of lean construction principles

Hypothesis

Table 9.1 (continued)

This means that the extent of reduction of construction wastes due to development of shared mental models will give an indication of the precast productivity performance. The leading indicator of precast productivity performance would be of higher risk of poor construction productivity if team members have a lower development of shared mental models. This is because the creation of conditions for team members to work together sets the baseline to ensure regular flow of activities and enhance the likelihood of achieving greater performance levels

This means that the extent of reduction in construction wastes due to the implementation of lean construction principles can give an indication of the precast productivity performance

9.3 Contributions to Knowledge and Practice 161

162

9 Conclusion and Recommendations

to come. Hence, contractors need to strengthen their fundamentals and understand the importance of team performance and streamline the manpower usage through implementation of lean in precast construction. This is to sustain the implementation of precast construction in Singapore such that contractors build up their precast construction capability not just at individual project level but at the enterprise level. Furthermore, this study have introduced the potential of having a leading indicator which is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator. This lagging indicator can only be known at the end of the project which will be too late. A leading indicator will help to track if the project is heading in the right direction and for improvements to be made while there is still time. There is a need for contractors to have a means to know its effectiveness and decide what and how to act if the level of productivity is low. This will also motivate the team to act proactively and not trail behind by simply relying on the reactive and delayed nature of the project productivity data to know where they stand. Hence, the proposed prediction model will allow better understanding of how lean principles can lead to reduction of construction wastes to lead to overall manpower reduction in precast construction projects. The proposed prediction model serves as a tool in assessing the total on-site and off-site productivity outcome of precast construction in the respective projects and gaining insights into how existing processes can be further enhanced to benefit precast construction projects. Further, the proposed prediction model will aid in the identification of missing conditions which the contractors need to improve on. The employment of lean construction practices is not only a solution to optimise manpower effort. Many problems such as the quality and safety of the projects whether under construction or after completion, late delivery, higher final cost, and accidents during construction can be minimised as well. Without lean construction management, all the manpower involved in precast construction will not be able to work together effectively. Therefore, it is critical that contractors make use of lean construction to reduce manpower effort throughout the precast construction process. Overall, this study will complement the BCA’s Construction Productivity Roadmaps and help contractors to determine how to drive both on-site and off-site manpower optimisation in precast construction.

9.4 Limitations of Study and Recommendations for Future Research This study has focused largely on manpower usage in precast construction from the contractor’s perspective in Singapore. However, lean construction should take place throughout the project lifecycle and requires the involvement of other stakeholders such as the owner, developer, and designer. Although it is plausible that the conceptual model may be applicable to these stakeholders, each firm may have different focus as

9.4 Limitations of Study and Recommendations for Future Research

163

well as a separate set of factors to be considered for lean construction implementation. Future research is encouraged to further investigate the differences with projects of a similar profile in other countries so as to derive stronger theoretical background for enabling lean in precast construction. The practicality of enabling lean in precast construction excluded monetary considerations. Thus, the results of this study should be interpreted taking to account these limitations which may answer for any anomaly observed. Hence, further research can be done using a larger dataset from different stakeholders which can also help to increase the accuracy of developing the leading indicator prediction model for the precast productivity performance. The scope of this study focuses on main contractor and precaster who manages the workers and hence would be in a direct position to impact the lean construction considerations through shared mental model development throughout the precast construction process. Future research could be done to ameliorate performance of the network by creating multiple networks to predict the manpower changes in each of the four stages—design, production, logistics and installation. This combined network results which requires responses from the other stakeholders such as consultants and the various subcontractors may give better predictions. This is a real-world proven method where the combined knowledge of these models will give a more accurate result than the knowledge of any single one of them. There is also trade confidentiality in the detailed productivity monitoring figures and project information and hence, it is acknowledged that the expected man-day utilised noted in this study may be slightly inaccurate as compared to using the actual man-day figures and including the possible influence of project characteristics.

9.5 Conclusion In conclusion, this research has provided the means to enable lean through shared mental models for precast construction to result in higher construction productivity. It is critical for team members to work together to reduce the occurrence of construction wastes to result in a leaner workforce and efficient process throughout the precast construction design, production, logistics and installation stages. The proposed conceptual model will be value-adding to contractors, providing them with a leading indication of the precast productivity performance to enable proactive improvements. The prediction model serves as a tool to gain insights into how existing processes can be further enhanced to drive precast construction capability and streamline both on-site and off-site man-day utilisation.

Appendix A

Details of Industry Practitioners

Consultation sessions were conducted with industry practitioners to seek their company’s views on precast construction as well as lean construction which are reflected in Chaps. 3 and 4 of this research. The conduct of these consultations was done in a face-to-face manner, phone call as well as email. All the practitioners have more than ten years of experience in the construction industry and have certain awareness of lean principles. Details of the practitioners can be found as follows: S/N

Company’s area of expertise

Practitioners’ designation/entity

Date of main interview

Mode of interview

1

A1 Main Contractor

Project Director

6 January 2017

Face-to-face

2

A1 Main Contractor

Design Manager

9 January 2017

Face-to-face

3

Developer

General Manager, Director and Technical Team

13 January 2017 Face-to-face

4

A1 Main Contractor

Executive Director

31 January 2017 Emails

5

A1 Main Contractor

Senior Manager

1 February 2017 Emails

6

A1 Main Contractor

Technical Director

2 February 2017 Emails

7

A1 Main Contractor

Technical Team

3 February 2017 Face-to-face

8

A2 Main Contractor

Director

4 February 2017 Emails

9

A1 Main Contractor

General Manager

7 February 2017 Emails

10

A2 Main Contractor

Senior Manager

24 March 2017

Face-to-face

11

A1 Main Contractor

Project Manager

27 March 2017

Emails

12

A1 Main Contractor

Technical Team

29 March 2017

Emails

13

A1 Main Contractor

Director

30 January 2018 Face-to-face

14

Precaster

General Manager

19 March 2018

Emails and Phone Calls

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

165

Appendix B

Pilot Survey Questionnaire

Dear Respondent, This survey is part of a research study on “Enabling Lean for Precast Construction in Singapore”. The objective is to understand the potential of reducing the total manpower requirements (both on-site and off-site) for precast construction projects. We value your inputs and contributions. All data collected in this survey will be used for purely academic purpose and will be kept strictly confidential in accordance with the Personal Data Protection Act. Please contact me if you have any questions or would like to know more about the aggregated survey findings. Thank you very much for your participation. Regards, Joy Ong (Ms): Department of Building: School of Design and Environment: National University of Singapore: 4 Architecture Drive: Singapore 117566. 1. General Information Company Name Company’s Construction Workhead for General Building (CW01) Tendering Limit

• • • •

A1—unlimited A2—up to S$85M B1—up to S$40M B2—up to S$13M

Number of Years of Experience in the Construction Industry (Please nominate these staffs/partner who are responsible for the following roles to participate in this survey) a. Project Manager

_______ years

b. Site Structural Engineer

_______ years

c. Architectural Coordinator

_______ years

d. M&E Coordinator

_______ years

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

(continued) 167

168

Appendix B: Pilot Survey Questionnaire

(continued) 1. General Information Company Name e. Precaster’s Representative

_______ years

2. Please provide the following information for all of your projects which fulfils the following three criteria: a. GFA ≥ 5000m2 ; b. Adopted precast construction; and c. Project completed after Year 2015.

Estimated total manpower savings (both ON-SITE and OFF-SITE) (%)

Constructability score

Buildable design score

Project productivity (m2 /man-day)

Constructed floor area (m2 )

Project length (months)

Project category

• Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 1 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 2 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 3 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 4 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 5 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 6

Appendix B: Pilot Survey Questionnaire 169

170

Appendix B: Pilot Survey Questionnaire

3. Please fill in the manpower usage for the above-mentioned projects. Trades

Manpower used (man-day) Project 1 Project 2 Project 3 Project 4 Project 5 Project 6

Site management team Basement Structure works Architectural works Building services and M&E works General External works Total On-Site Manpower Used (man-day) [To be obtained from your Electronic Productivity Submission System (ePSS) submissions.] Assembly of moulds, mould cleaning and preparation Fixing of rebars/cast-in items/prestressing strands Installation of M&E services e.g. conduits and pipes, testing, etc. Final inspection before casting, concreting and curing, demoulding, etc. Transfer to storage yard Finishing works (including PBU tiling, waterproofing, etc.) Transportation to site including loading onto trailer Total Off-Site Manpower Used (man-day)—includes trade installer, machine operator and safety & health workers [to be obtained from your precaster.]

Appendix B: Pilot Survey Questionnaire

171

4. As the Project Manager/Site Structural Engineer/Architectural Coordinator/M&E Coordinator/Precaster, rate the level of expected changes in the occurrence of construction wastes during the precast construction process (design, production, logistics and installation) resulting from the following statements. Note: Construction wastes refer to defects and rework, overproduction, waiting and idle time, non-utilised resources, transportation, inventory, motion and extraprocessing. Where: 1 = Moderate increase; 2 = Slight increase; 3 = About the same; 4 = Slight reduction; 5 = Moderate reduction; 6 = Major reduction; 7 = Extreme reduction (Each member shall tick at the corresponding box for each row.)

We observe and understand the process

Alternative solutions are considered

We continuously review the process

Team members reconcile conflicts and reconfirm goals

Team members develop introspective practices

Team members share information that is previously possessed individually by each team member to others in the team

14

15

16

17

Operations are adapted accordingly

8

13

We can visualise the entire process

7

12

Tasks are standardised

6

We seek to grow together with solid subcontractors and suppliers

When there is problem, we will stop to fix it immediately

5

11

Workload is levelled out

4

We empower our people

Pull-replenishment is used

3

We develop our people

There is creation of one-piece flow

2

9

There is focus on long-term results

1

10

Statements

S/N 4

5

6

7

2

3

4

1

3

1

2

Site structural engineer

Project manager 5

7

(continued)

6

172 Appendix B: Pilot Survey Questionnaire

Statements

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

Team members integrate information and determine the consequences

Team members have a common goal and form compatible expectations to act accordingly

Team members collaborate and work closely through a structured means of communication

Team members are committed and motivated to meet the client’s needs.

Cross-training to equip team members with a shared knowledge of their teammates’ work

Team members get another’s information requirement accurately and quickly

S/N

18

19

20

21

22

23

24

(continued) 5

6

7

2

3

4

1

4

Site structural engineer

3

1

2

Project manager 5

6

7

Appendix B: Pilot Survey Questionnaire 173

We observe and understand the process

Alternative solutions are considered

We continuously review the process

Team members reconcile conflicts and reconfirm goals

Team members develop introspective practices

Team members share information that is previously possessed individually by each team member to others in the team

14

15

16

17

Operations are adapted accordingly

8

13

We can visualise the entire process

7

12

Tasks are standardised

6

We seek to grow together with solid subcontractors and suppliers

When there is problem, we will stop to fix it immediately

5

11

Workload is levelled out

4

We empower our people

Pull-replenishment is used

3

We develop our people

There is creation of one-piece flow

2

9

There is focus on long-term results

1

10

Statements

S/N 4

5

6

7

2

3

4

1

3

1

2

M&E coordinator

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

7

(continued)

6

174 Appendix B: Pilot Survey Questionnaire

Statements

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

Team members integrate information and determine the consequences

Team members have a common goal and form compatible expectations to act accordingly

Team members collaborate and work closely through a structured means of communication

Team members are committed and motivated to meet the client’s needs

Cross-training to equip team members with a shared knowledge of their teammates’ work

Team members get another’s information requirement accurately and quickly

S/N

18

19

20

21

22

23

24

(continued) 5

6

7

2

3

4

1

4

M&E coordinator

3

1

2

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

6

7

Appendix B: Pilot Survey Questionnaire 175

176

Appendix B: Pilot Survey Questionnaire

5. As the Project Manager/Site Structural Engineer/Architectural Coordinator/M&E Coordinator/Precaster, rate the expected changes in the manpower used (both ON-SITE and OFF-SITE) during the precast construction process (design, production, logistics and installation) resulting from minimisation of the following scenarios. Note: Where: 1 = Moderate increase; 2 = Slight increase; 3 = About the same; 4 = Slight reduction; 5 = Moderate reduction; 6 = Major reduction; 7 = Extreme reduction (Each member shall tick at the corresponding box for each row.)

Scenarios

Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes

Minimisation of extra-processing due to design changes

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

Minimisation of non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

Minimisation of motion from the arrival of precast components at site to hoisting

Minimisation of non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

S/N

1

2

3

4

5

6

7

8

9

10

4

5

6

7

2

3

4

1

3

1

2

Site structural engineer

Project manager 5

7

(continued)

6

Appendix B: Pilot Survey Questionnaire 177

Scenarios

Minimisation of overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

S/N

11

(continued) 5

6

7

2

3

4

1

4

Site structural engineer

3

1

2

Project manager 5

6

7

178 Appendix B: Pilot Survey Questionnaire

Scenarios

Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes

Minimisation of extra-processing due to design changes

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

Minimisation of non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

S/N

1

2

3

4

5

6

7

4

5

6

7

2

3

4

1

3

1

2

M&E coordinator

Architectural coordinator 5

6

7

1

2

Precaster 3

4

6

7

(continued)

5

Appendix B: Pilot Survey Questionnaire 179

Scenarios

Minimisation of motion from the arrival of precast components at site to hoisting

Minimisation of non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

Minimisation of overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

S/N

8

9

10

11

(continued) 5

6

7

2

3

4

1

4

M&E coordinator

3

1

2

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

6

7

180 Appendix B: Pilot Survey Questionnaire

Appendix B: Pilot Survey Questionnaire

181

6. Comments/Feedback (if any).

–END–

Appendix C

Final Survey Questionnaire

Dear Respondent, This survey is part of a research study on “Enabling Lean for Precast Construction in Singapore”. The objective is to understand the potential of reducing the total manpower requirements (both on-site and off-site) for precast construction projects. This survey should take approximately 20 minutes to complete. We value your inputs and contributions. All data collected in this survey will be used for purely academic purpose and will be kept strictly confidential in accordance with the Personal Data Protection Act. Please contact me if you have any questions or feedback. Thank you very much for your participation. Regards, Joy Ong (Ms): Department of Building: School of Design and Environment: National University of Singapore: 4 Architecture Drive: Singapore 117566.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

183

184

Appendix C: Final Survey Questionnaire

*Please read following three slides to understand the general background information of this research study before proceeding:

Appendix C: Final Survey Questionnaire

185

**Please read the following glossary which will help you to answer the questions before proceeding: What are Construction Wastes? Construction wastes

Causes

Defects and rework

Defects and rework due to errors in design Defects and rework due to non-conformance Defects and rework due to changes

Overproduction

Early production of elements before they are needed

Waiting and idle time

Waiting for sending elements to construction site and at the construction site Waiting for approvals Waiting for inspection of elements

Non-utilised resources

Poor utilisation of workforce time and talent due to jobs and skill mismatch Poor utilisation of workforce time and talent due to insufficient training

Transportation

Unnecessary transportation of equipment and materials

Inventory

Excessive materials more than planned requirements, consuming floor space Elements undergoing inspection, increasing lead time

Motion

Unnecessary movements of equipment, materials and staffs due to inappropriate site layout

Extra-processing

Unnecessary processes leading to wastes of materials and equipment

186

Appendix C: Final Survey Questionnaire

What is Lean Construction? Lean construction is a way of designing the process flow and working methodology to minimise wastes to provide better value for the client (Ballard and Howell 2003; Koskela et al. 2002; Cagliano et al. 2006) Lean Principles

Brief

Focus on long-term results

To grow and align the whole organisation towards a common purpose

Create continuous process flow to bring problems to the surface

To have a process in place to manage any issues immediately and ensure zero time spent sitting idle or waiting for someone to work on the task

Use “Pull” systems to avoid overproduction To manage materials just-in-time with minimum inventory Level out the workload

To avoid stop-start approach of working and get ready for applying “Pull”

Build a culture of stopping to fix problems, to get quality right the first time

To have a management system with the capability of detecting problems, stopping to solve problems and putting in place countermeasures going forward

Standardise tasks as a foundation for continuous improvement

To follow a uniform method whenever the same task is being performed

Use visual control throughout the process so no problems are hidden

To help someone determine immediately when there are deviations

Adapt operations to suit technology, people and processes

To deconflict and become accustomed to the new approach

Empower your people

To make team members lead and teach others the way of doing the tasks

Develop your people

To train team members that work well with the organisation’s vision

Grow together with solid subcontractors and suppliers

To respect and treat them as an extension of your business

Go and see for yourself to thoroughly understand the situation

To think and speak based on personal understanding

Make decisions slowly by consensus, thoroughly considering all options and implement decisions rapidly

To thoroughly consider alternatives before making any decisions

Review processes for continuous improvement

To reflect at key milestones to identify the shortcomings and develop countermeasures to avoid the same mistakes again

What is Shared Mental Models? Shared mental models are knowledge structures held by members of a team that enable them to form accurate explanations and expectations for the task,

Appendix C: Final Survey Questionnaire

187

and, in turn, to coordinate their actions and adapt their behaviour to demands of the task and other team members (Converse et al. 1993).

START OF SURVEY: 1. General Information Company Name: Company’s Construction Workhead for General Building (CW01) Tendering Limit

• • • •

A1—unlimited A2—up to S$85M B1—up to S$40M B2—up to S$13M

Name and Number of Years of Experience in the Construction Industry [Please nominate these five staffs/partners who are responsible for the following roles (or equivalent) to participate in question 4 and 5 of this survey.] a. Project Manager:

_______ years

b. Site Structural Engineer:

_______ years

c. Architectural Coordinator:

_______ years

d. M&E Coordinator:

_______ years

e. Precaster’s Representative:

_______ years

188

Appendix C: Final Survey Questionnaire

2. Please provide the following information for all of your projects which fulfils the following three criteria: a. GFA ≥ 5000m2 ; b. Adopted precast construction; and c. Project completed after Year 2015.

Project productivity (m2 /man-day)

Constructed floor area (m2 )

Project length (months)

Project category

• Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 1 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 2 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 3 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 4 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 5 • Public Housing (HDB Projects) • Commercial • Residential (landed) • Industrial • Residential (non-landed) • Institutional

Project 6

Appendix C: Final Survey Questionnaire 189

190

Appendix C: Final Survey Questionnaire

3. Please fill in the manpower usage for the above-mentioned projects. Trades

Manpower used (man-day) Project 1

Project 2

Project 3

Project 4

Project 5

Project 6

Site management team Basement Structure works Architectural works Building services and M&E works General External works Total On-Site Manpower Used (man-day) [To be obtained from your Electronic Productivity Submission System (ePSS) submissions.]

4. Based on your experience in precast construction projects, what were the changes in the occurrence of construction wastes during the precast construction process (i.e. design, production, logistics and installation stages) resulting from implementation of the following statements? Where:

(Each member shall tick at the corresponding box for each row.)

Statements

Go and see for yourself to thoroughly understand the situation

Make decisions slowly by consensus, thoroughly considering all options and implement decisions rapidly

Review processes for continuous improvement

13

14

Adapt operations to suit technology, people and processes

8

Grow together with solid subcontractors and suppliers

Use visual control throughout the process so no problems are hidden

7

12

Standardise tasks as a foundation for continuous improvement

6

11

Build a culture of stopping to fix problems, to get quality right the first time

5

Empower your people

Level out the workload

4

Develop your people

Use “Pull” systems to avoid overproduction

3

10

Create continuous process flow to bring problems to the surface

2

9

Focus on long-term results

1

Lean principles

S/N 4

5

6

7

2

3

4

1

3

1

2

Site structural engineer

Project manager 5

7

(continued)

6

Appendix C: Final Survey Questionnaire 191

Statements 5

6

7

2

3

4

1

4

Site structural engineer

3

1

2

Project manager 5

6

Team members reconcile conflicts and reconfirm goals

Team members develop introspective practices

Team members share information that is previously possessed individually by each team member to others in the team

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

Team members integrate information and determine the consequences

Team members have a common goal and form compatible expectations to act accordingly

Team members collaborate and work closely through a structured means of communication

Team members are committed and motivated to meet the client’s needs

Cross-training to equip team members with a shared knowledge of their teammates’ work

Team members get another’s information requirement accurately and quickly

15

16

17

18

19

20

21

22

23

24

Shared mental models (Note: Team members refers to Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and Precaster)

S/N

(continued) 7

192 Appendix C: Final Survey Questionnaire

Statements

Go and see for yourself to thoroughly understand the situation

Adapt operations to suit technology, people and processes

8

12

Use visual control throughout the process so no problems are hidden

7

Grow together with solid subcontractors and suppliers

Standardise tasks as a foundation for continuous improvement

6

11

Build a culture of stopping to fix problems, to get quality right the first time

5

Empower your people

Level out the workload

4

Develop your people

Use “Pull” systems to avoid overproduction

3

10

Create continuous process flow to bring problems to the surface

2

9

Focus on long-term results

1

Lean principles

S/N 4

5

6

7

2

3

4

1

3

1

2

M&E coordinator

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

7

(continued)

6

Appendix C: Final Survey Questionnaire 193

Make decisions slowly by consensus, thoroughly considering all options and implement decisions rapidly

Review processes for continuous improvement

13

14

5

6

7

2

3

4

1

4

M&E coordinator

3

1

2

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

Team members reconcile conflicts and reconfirm goals

Team members develop introspective practices

Team members share information that is previously possessed individually by each team member to others in the team

Team members discuss on possible actions and improvements, identify significant risks and prioritise actions to address them

Team members integrate information and determine the consequences

Team members have a common goal and form compatible expectations to act accordingly

15

16

17

18

19

20

6

7

(continued)

Shared mental models (Note: Team members refers to Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and Precaster)

Statements

S/N

(continued)

194 Appendix C: Final Survey Questionnaire

Statements

Team members collaborate and work closely through a structured means of communication

Team members are committed and motivated to meet the client’s needs

Cross-training to equip team members with a shared knowledge of their teammates’ work

Team members get another’s information requirement accurately and quickly

S/N

21

22

23

24

(continued) 5

6

7

2

3

4

1

4

M&E coordinator

3

1

2

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

6

7

Appendix C: Final Survey Questionnaire 195

196

Appendix C: Final Survey Questionnaire

5. Based on your experience in precast construction projects, what were the changes in the manpower used (both ON-SITE and OFF-SITE) in man-day during the precast construction process (i.e. design, production, logistics and installation stages) as a result of the following scenarios? Where:

(Each member shall tick at the corresponding box for each row.)

Minimisation of extra-processing due to design changes

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

2

3

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

Minimisation of non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

5

6

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

Minimisation of motion from the arrival of precast components at site to hoisting

7

8

Logistics

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

4

Production

Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes

Scenarios

1

Design

S/N 4

5

6

7

2

3

4

1

3

1

2

Site structural engineer

Project manager 5

7

(continued)

6

Appendix C: Final Survey Questionnaire 197

Scenarios

Minimisation of non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

Minimisation of overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

9

10

11

Installation

S/N

(continued) 5

6

7

2

3

4

1

4

Site structural engineer

3

1

2

Project manager 5

6

7

198 Appendix C: Final Survey Questionnaire

Scenarios

Minimisation of extra-processing due to design changes

Minimisation of defects and rework due to due to improper interfacing between precast components resulting in extra-processing

2

3

Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory

Minimisation of waiting and idle time due to the need to conduct a thorough quality control and assurance procedure in precast construction which contributes to inventory

Minimisation of non-utilised resources due to incompetency of workforce to perform precast construction causing defects and rework

4

5

6

Production

Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes

1

Design

S/N 4

5

6

7

2

3

4

1

3

1

2

M&E coordinator

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

7

(continued)

6

Appendix C: Final Survey Questionnaire 199

Scenarios

Minimisation of motion from the arrival of precast components at site to hoisting

8

Minimisation of non-utilised resources due to the lack of knowledge sharing and learnings, lack of training, poor communication and unclear scope and deliverables in precast construction

Minimisation of defects and rework due to non-compliance to quality requirements of precast construction

Minimisation of overproduction due to the lack of accurate planning preparations in precast construction causing extra-processing

9

10

11

Installation

Minimisation of waiting and idle time and transportation for the delivery of precast components across multiple sites

7

Logistics

S/N

(continued) 5

6

7

2

3

4

1

4

M&E coordinator

3

1

2

Architectural coordinator 5

6

7

1

2

Precaster 3

4

5

6

7

200 Appendix C: Final Survey Questionnaire

Appendix C: Final Survey Questionnaire

201

6. Comments/Feedback (if any). _______________________________________________________________ _______________________________________________________________ –END–

Appendix D

Guiding Questions Used For Interviews

What are your views on these seven observations gathered from the survey? 1. Key members responsible for the following roles or equivalent (Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster) were asked to rate the expected changes in the occurrence of construction wastes during the precast construction process (i.e. from design to on-site installation) because of shared mental models and lean principles implementation (refer to the Glossary provided in the survey).

Observation 1a–1c: The top three attributes resulting in reduction in occurrence of construction wastes are: a. ‘Create continuous process flow to bring problems to the surface’ b. ‘Build a culture of stopping to fix problems, to get quality right the first time’ c. ‘Focus on long-term results’ These three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. 2. Key members responsible for the following roles or equivalent (Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster) were asked to rate the expected changes in the total manpower used (both on-site and off-site) during the precast construction process resulting from minimisation of the construction wastes. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

203

204

Appendix D: Guiding Questions Used For Interviews

Observation 2a–2c: The top three attributes resulting in the highest reduction in the manpower utilisation are: a. ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ b. ‘Minimisation of extra-processing due to design changes’ c. ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’ These three attributes were generally rated to result in between 10 and 20% less man-day during the precast construction process. 3. Observation 3: When reduction of construction wastes due to the implementation of lean construction principles is observed, reduction of construction wastes due to the development of shared mental models will also be observed. 4. Observation 4: When reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. 5. Observation 5: When reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total man-days used will also be observed. 6. Observation 6: Generally, responses from the various roles were rather consistent. 7. Observation 7a–7b: This study introduces the potential of having a leading indicator which is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator. This lagging indicator can only be known at the end of the project which will be too late. A leading indicator will help to track if the project is heading in the right direction and for improvements to be made while there is still time. The leading indicator in this study measures the contractor’s ability to manage precast construction projects in a lean environment, which covers minimisation of construction wastes to reduce the man-days utilised. a. Precast productivity performance can be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. b. Precast productivity performance can be predicted based on the extent of reduction of construction wastes due to the development of shared mental models. –END—

Appendix E

Verbatim Report With Mr. A

This is an interview transcript with Mr. A (Precaster) on the 4 November 2019, 10 am to 10.55 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: Hello, since we last conversed, I have done a survey with 32 companies and the objective of this session is to seek your views on the key observations and results gathered from my survey. My study is about enabling lean using shared mental models for precast construction in Singapore. Are you familiar with the term “lean construction” and “shared mental models”? Mr. A: Actually, I have read through the document which you have sent over. This is the first time I am hearing these terms. What does it mean? J: Lean originated from production management principles developed by Toyota in the 1950s. Lean is a way of designing process flow and methodology to minimise wastes and enhance productivity. Wastes, in construction, refers to defects and rework, overproduction, waiting and idle time, non-utilised resources, transportation, inventory, motion and extra-processing, as shown in this table (refers to the document printed out). By reducing construction wastes, construction productivity should improve. In my study, productivity includes both on-site and off-site man-days, unlike BCA’s definition which only takes into consideration on-site man-days. Mr. A: Oh. These days, construction productivity have improved due to the shift to precast. Definitely, site productivity have improved with the adoption of precast but site workers have shifted to the factory. Even these off-site workers in the factory are included in the calculation, the total manpower used should still be lower than before. This is because works are now being done in a factory-controlled environment which makes things easier to manage.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

205

206

Appendix E: Verbatim Report With Mr. A

1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. A: This point does encourage the team to come together to quickly resolve any problem or the schedule of the entire process will be affected. Normally, problems that surfaced downstream in the production line are minor quality issues and we just have to make some adjustments before continuing with he works. 2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment? Mr. A: We believe in getting quality right the first time too. Depending on the complexity of project, we do send our engineers to our factory in Malaysia to inspect the production, ensure that things are done correctly and quality is up to standard. We do not just rely on the client’s representatives to do such inspection. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. A: For the project sake or working relationship with our customer—the main contractor, we do give advice on the issues to take note of during site installation. Hence, we do think long-term as in what happens after our responsibility ends. To remove construction wastes, things like studying the lifting plan, the tower crane capacity which is dependent on the loading of the biggest precast component and the span. Rental of these equipment are very expensive and there would be big problem if they only discover that the precast components could not be lifted up during on-site installation. Or if there is a need for mobile crane or not. By right, this should be the duty of the main contractor to plan but contractors these days do not seem to spend some time to check such details and just proceed with the works. It could be due to manpower issue or a tight construction schedule. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-days utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-days if avoided. Do you agree? Mr. A: Yes, the architect plays a very strong role as their design would affect how many columns and beams we can standardise which in turn affects the productivity.

Appendix E: Verbatim Report With Mr. A

207

I currently have one project in which I have to assign seven engineers to work on it as the design is not standardised which complicates our work. We are usually brought into the project quite late. Ideally, our detailing inputs should be sought six months before the production schedule. The structural consultant would have to meet the minimum buildability score and the main contractor would have to meet the minimum constructability score. All these have to be planned upfront to prevent the occurrence of construction wastes and reduce some manpower usage. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’ which may be initiated by the client or consultants due to coordination issues with the various disciplines which should have been initiated earlier. Mr. A: This is something that is seen in all projects. So yes, if such design changes can be avoided, it would help to reduce the man-days. 6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. A: Overproduction may happen as our production lines may be producing elements for several projects at the same point in time which may cause confusion. But this is not very frequent although we still see such incidents happening. So if overproduction can be eliminated, the man-effort required would definitely be more optimised. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. A: The reduction in construction wastes would be obvious if team members are able to work together throughout the entire process to consider all issues from the start to the end. People always think that they still have time to work on it later on, during the next coordination meeting for example, when they are pressed for an answer. When they want to act on it and think of alternative solutions for example, it may be too late. J: How about you, as the precaster, being a key team member in precast construction? Mr. A: We need to have a strong drafting team, able to foresee downstream problems during production and connection issues. Once the shop drawings are not correct, there would be rework at the precast yard and even on-site. There are still some minor reworks here and there such as chipping off during demoulding.

208

Appendix E: Verbatim Report With Mr. A

In the factory, we have an established process to ensure that things are properly controlled, even material wastage. J: I understand that the scope of a precaster typically ends once the precast components are delivered to site and the main contractor would have to take over from here. What issues have you faced which resulted in unproductive work? Mr. A: In Singapore, most of the sites are very tight and there are no space or holding area for storage of the precast components. We have to work with the contractor on the schedule and do just-in-time delivery. This is very challenging due to traffic jams and custom clearance. Sometimes, the driver had to wait hours outside the site due to site coordination issues and they are not ready to unload and install. Our driver can only go back to Malaysia after they have unloaded. We also do installation on-site for some projects with specialised precast works and our workers had to wait on-site from morning till late afternoon as the precast components have not arrived. J: Would it be more effective if a precaster also manages the installation on-site since you came out with the shop drawings and would be able to seamlessly coordinate? Mr. A: Of course. However, we cannot fight with many of these precast installation subcontractors. Our pricing would never beat them as they have very little overheads, unlike here as you can see in our office. We specialised in the posttensioning sector and also started to be a precaster when the industry shifted to precast construction. 8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. A: For precast work which are just re-bar, formwork, casting, mould fabrication, the workers basically just follow what have been communicated to them. Workers need to be closely guided. If there are any mistakes, they just do again which means more man-hours would be required. So the people who give instructions to these workers are very important for man-days reduction to happen. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. Do you think so too? Mr. A: Yes, for example, the project manager needs to coordinate with his subcontractor, consultant and precaster to direct the workers what to do and get the job done. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster.

Appendix E: Verbatim Report With Mr. A

209

Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding? Mr. A: This shows that people are aware of the benefits of lean and shared mental models. It is good sign that they do communicate and understand what is happening or what should be happening. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces the potential of having a leading indicator which is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to track and benchmark how they can improve their productivity. What is your view on this? Mr. A: This would be useful for contractors to plan and control the project. However, I feel that this can only be used as a guide as the figures are unlikely to be accurate, just like BCA’s site productivity figures. For BCA, though there is biometric to track the on-site man-day utilised, I think it is not very accurate. I have done such submissions before and feel that it is not very accurate as the workers, in particular, those involved in several trades, are not accurately accounted to the correct category of the work they are involved in throughout the day at site. For example, the workers may be counted under “General Workers” even though they are also performing “Structural Works” and even “External Works”. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models? Mr. A: Same as what I said earlier, this can only be used as a guide as the figures are unlikely to be accurate. J: Thank you for your feedback. That is all I have. Thank you for taking time to participate in this interview session. Mr. A: No problem. I hope you have gained a better understanding of how the precast construction industry works for your study. End of Transcript.

Appendix F

Verbatim Report With Mr. B

This is an interview transcript with Mr. B (Main Contractor) on the 5 November 2019, 9 am to 9.50 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: Good morning. I am a researcher from NUS and the objective of this interview is to seek your views on the key observations and results gathered from my survey conducted with 32 companies. My email have summarised what is my research about which is enabling lean using shared mental models for precast construction in Singapore. Are you familiar with the term “lean construction” and “shared mental models”? Mr. B: Yes, I have heard of lean construction from BCA. I feel that the shared mental model mentioned is all about communication. In our company, the project manager have a very strong power and have to manage the entire project. We have done many types of precast projects such as hospital, residential and commercial. Most of them are design and build while few of them are build-only. 1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. B: The contractor plays a very important role here to manage this process. We have technical engineers to check the shop drawings before installation but there are situations where problems only surfaced during physical installation on-site. As a result, the precast component had to be sent back to Malaysia which means time and manpower wastage. In the past, when we were still able to get our precast components produced from factory in Singapore, the quality is alright. Nowadays, © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

211

212

Appendix F: Verbatim Report With Mr. B

everything is done in the Malaysia factory and the quality and system in-place is not as high as Singapore. J: Why is this the case? Mr. B: This could be because there is no mandatory requirement for precaster to get their factories to be accredited by the Singapore Concrete Institute. The precaster accreditation is important to ascertain that the precaster’s factory have been audited to meet certain quality standards. For us, we send our own staffs over to do periodic inspection to ensure the quality. In general, contractors may or may not do so. Strictly speaking, the client should engage the RE or RTO to do such inspections but this is not the usual practice as it is very hard to find a good RE or RTO to station at Malaysia and do such inspection for the client. 2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment on this? Mr. B: During the design stage, it is important that the shop drawings are correct. We will submit the shop drawings and get the consultant to check. This is a critical point to check. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. B: For us, we will study the preliminary design given during tendering stage and work with our consultants to see how to value add, considering downstream buildability and constructability issues. This is called value engineering. Sometimes, the design is over-specified and we will propose an alternative proposal which is cheaper and/or faster to construct. But such methods are usually more expensive and the client would have to weigh which option is preferred. For commercial projects, they will be able to lease out the space earlier and collect revenue earlier. We will also bring in the precaster during tendering stage to look into the possibility of further standardising the design. But for build only projects, it is harder to do so and think about the long-term results as most of the items are fixed already. For cost effectiveness, precaster will want to standardise as much as possible but the architect have very strong power and may not approve the standardisation. This results in more man-effort incurred which translates into higher cost. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-days utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility

Appendix F: Verbatim Report With Mr. B

213

of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-days if avoided. Do you agree? Mr. B: I have mentioned some of these points earlier. To optimise manpower utilisation, we will plan for the delivery of the precast components to arrive onsite early in the morning. We also asked our workers to come in early, around the same time. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’ which may be initiated by the client or consultants due to coordination issues with the various disciplines which should have been initiated earlier. Mr. B: Extra-processing may happen due to time constraint. Sometimes, we had to ask the precaster to proceed even before obtaining the consultant’s approval. This have caused some reworks downstream due to changes to the design. 6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. B: For precast works, we have to work closely with the precaster to follow the on-site construction sequence, floor by floor. However, precaster typically prefers to complete the casting for all same type of components at one go for efficiency. If this is the case, the precaster would have to have a holding area at their precast yard to store these precast components first as the site would not have space for early delivery of these items. The precaster’s ideal fabrication sequence would not match the site installation sequence. In such cases, two-way communication is required to work out a win-win solution for both parties. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. B: This is true but may not be substantial. In lean, if a certain portion of work cannot be done, the next work cannot start and there is a need to inform everybody and work out the revised design and approach. In practice, though many of the things are done just-in-time, just like lean, sometimes, it is too late by the time the information is passed down. The man-effort would have been incurred and wastes would have occurred. For reduction of construction wastes to be substantial, I think manpower preparation and coordination among all team members are important. Frequent communication and site monitoring is also very important to remove wastes and reduce man-effort.

214

Appendix F: Verbatim Report With Mr. B

8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. B: Just like what I mentioned earlier, this is correct but the reduction may not be substantial. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. Do you think so too? Mr. B: Yes, we believe that when our people work together with the company to do well and successfully complete every project, there should be improvement such as better work efficiency and higher quality of works. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster. Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding? Mr. B: This sounds good, shows that team members are aware of the inadequacy and how they can improve if they practice lean and develop their shared mental model in every project. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces a leading indicator for precast productivity performance which will be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. This is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to benchmark how they can improve their productivity. What is your view on this? Mr. B: I think it is important that the leading indicator would be something that contractors can benchmark themselves against others and know where they fall short. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models? Mr. B: This seems to rely on the team member’s self-assessment which may be one-sided. But I think contractors, who genuinely want to make something out of this number, will make the assessment based on the actual situation.

Appendix F: Verbatim Report With Mr. B

215

J: I think I have no further questions. Thank you for taking time to participate in this interview session. Mr. B: No problem. All the best for your study. End of Transcript.

Appendix G

Verbatim Report With Mr. C

This is an interview transcript with Mr. C (Precaster) and two team members on the 12 November 2019, 9.15 am to 10.15 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: Good to meet you again. Since we last met, I have done a survey with 32 companies and the objective of this session is to seek your views on the key observations and results gathered from the survey. To recap, my study is about enabling lean using shared mental models for precast construction in Singapore. It is about reducing construction wastes to reduce the total man-day utilised and having team members working together throughout the precast construction process to reduce the total man-day. Mr. C: I see. For precaster, we are right at the bottom of the supply chain. For lean construction to work, it should be done right from the top, that is, the client, designer, main contractor, etc. In reality, there is often no time which results in what you call construction wastes. The shift to precast construction from cast insitu is simply shifting the works off-site. The designer and contractors and even the client need to better understand how precast construction works so that the entire project team can work together more efficiently. 1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. C: I think this is important. For us, our draftsmen will do up the shop drawings, then our engineers will check to ensure compliance with the consultants drawings. If this process is not in place, we would have big problem during production as once © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

217

218

Appendix G: Verbatim Report With Mr. C

the shop drawings are used for production, the rectification later on, if anything is found to be wrong, would be very tough. 2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment? Mr. C: I think this is not much of an issue if the shop drawings are correct. The rest of the process at our precast yard are quite ok and the client’s appointed RTO are also stationed at the precast yard to do quality inspections. It also depends on the RTO’s supervising experience and capability. If the client is willing to pay more, engaging a RE to station at the precast yard would be better. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. C: This really depends on the project design. Although there is a need to meet a minimum buildability score, in practice, the consultants and main contractor would have to strike a balance. For example, it is better to standardise the beam size to be more productive. However, the design may not require such a big beam size for all areas. Cost wise, it is also not beneficial to over-design. As result, we have no choice but have to accept the many type of variants given to us to produce. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-day utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-day if avoided. Do you agree? Mr. C: Again, this depends on the design, how much can be standardised. For fixed mould, there is not much of a problem downstream. What we observed is that when adjustable mould is used, there may be quality issues of chipping during demoulding and extra man-effort is required for touching up. From an engineering perspective, it would be best if cast in-situ is used if the design cannot be standardised as there is no value in doing so, except lesser man-days would be incurred with the use of precast. Moreover, precast is more costly than cast in-situ. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’. Mr. C: This is a frequent occurrence. When the consultants make any changes due to the client’s request, coordination issues with the various disciplines, etc., we have no time to react, resulting in extra-processing which could be avoided. We

Appendix G: Verbatim Report With Mr. C

219

also have limited say to propose a more cost effective and standardised proposal as the design is fixed. The amount of extra-processing incurred would depend on whether production have started and how much we have worked on the shop drawings. 6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. C: We typically discuss the construction schedule with the contractor and produce accordingly. As the mould takes up huge space at our precast yard, we may need all precast components which are using the same mould to be completed together. We have a few production cycles and are still able to prioritise the site construction schedule. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. C: From my experience, the extent of such occurrences is more prominent in mega projects. All key personnel would be stationed at the site office, solely working on this particular project and are able to discuss on the spot and resolve the problem. For smaller-scale projects, I think that the main contractor plays an important role to coordinate among the consultants, subcontractors, etc. The project manager should ensure that the BIM model is always updated once there are any changes and identify the impact, whether there are any clashes, constructability issues, etc. Unless the project manager is very good and experienced, problems may only be discovered during on-site installation which will be too late. 8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. C: I agree, but sometimes, we put in buffer which incurs more manpower to cater for some risks. On top of the consultants design, we may have to add additional shear links, concrete cover, etc. to prevent cracking to account for the dynamic loading during transportation and lifting, as well as to act as lifting anchorage. Some may feel that this is considered wastes. Or things like some consultants require the steel to be produced in Singapore. But our precast yard is in Malaysia, so the steel would have to be exported to Malaysia and imported back to Singapore after it is casted with the concrete. To add on, we also faced issues during custom clearance such as tax issues and the precast components can

220

Appendix G: Verbatim Report With Mr. C

only be released to be delivered to site after such issues are settled. This resulted in waiting time and the driver can only go back to Malaysia to make the next batch of delivery after sending the items to site and unloading by the contractor. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. What is your view? Mr. C: For projects in which the design is optimally standardised, this is possible. For projects in which the design is not standardised and yet precast construction is still required, the reduction in the total man-days used may not happen. For example, the supervisors at the precast yard may do a thorough check on one beam for each variant. Checking ten variants versus checking hundreds of variants, the man-effort incurred would be greatly different and to be productive. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster. Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding? Mr. C: Ultimately, meeting the end-date of the project is most important and all of these team members should be aware and will want to work together collaboratively and practice lean. They definitely understand the situation, especially the experienced ones, though may have difficulties practicing it due to the client’s design, cost, regulations, etc. Also, it is also dependent on individual as some people prefer to do things in a certain way and do not want to change. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces a leading indicator for precast productivity performance which will be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. This is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to benchmark how they can improve their productivity. What is your view on this? Mr. C: This may be useful if contractors want to improve their productivity. But one thing that is often overlooked is temporary works which also affects productivity too. Things like lifting design, lifting equipment capacity and layout, propping, etc. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models?

Appendix G: Verbatim Report With Mr. C

221

Mr. C: It should be about the same as it boils down to the design and how contractors manage the project productivity. Sometimes, for large precast components, the contractor will do casting at the on-site yard as there are challenges to transport the huge precast item and is riskier. They will weigh the pros and cons, whether there is space on-site and whether it is cost effective as they will need to incur cost to set-up the on-site yard but will save on logistics cost. J: That is the last question. Thank you for taking time to participate in this interview session. Mr. C: Thank you for your time too. End of Transcript.

Appendix H

Verbatim Report With Mr. D

This is an interview transcript with Mr. D (Main Contractor) and two team members on the 12 November 2019, 11 am to 11.45 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: My name is Joy and I am currently doing a research study on enabling lean using shared mental models for precast construction in Singapore. I met up with another of your colleague previously and she provided me with valuable inputs which helped to shape the scope of my study. The scope of my study is about reducing construction wastes to reduce the total man-days utilised and having team members working together throughout the precast construction process to reduce the total man-days. I have done a survey with 32 companies and the objective of this session is to seek your views on the key observations and results gathered from the survey. Mr. D: Just to note there are different types of precast construction, like PPVC, PBU, normal precast beam, slab, panel and our response will be slightly different based on our experience which is mostly residential projects. 1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. D: We have not really faced much construction wastes as the design in most of our projects are standardised. We will work together with the consultants to refine the types of precast variants. Even for private residential projects, though the architect have more freedom to design, we will work together with the consultants to explore how to standardise as far as possible. There is a time period allocated for such coordination before the first production in the factory. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

223

224

Appendix H: Verbatim Report With Mr. D

2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment? Mr. D: Generally, there are no major issues that require us to really stop work. We have a standard process in place to check for problem before proceeding to the next activity. I think most contractors should have such a process as they should have obtained ISO quality certification. But whether it is strictly followed by all of their people and in all of their project is another question. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. D: Yes, this is important. We have coordination meetings frequently to foresee downstream problem and sort out any issues. As the main contractor, it is to our advantage to think long-term as we will be affected in the end, being the main party responsible to the client. However, there are still times where project is not controlled and monitored closely and there is delay in information being passed down to the actual person who needs to make the changes. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-days utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-days if avoided. Do you agree? Mr. D: Yes, the most important phase is upfront, during design, till the first structure production. Everybody have to coordinate, think ahead and be committed on the project. For example, items in which there is no repetition, we will plan for it to be done cast in-situ. The more times the moulds are being re-used, the lesser man-days would be required. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’. Mr. D: We do not encounter much changes which will affect precast works. Typically, it is more on M&E and architectural works. 6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’.

Appendix H: Verbatim Report With Mr. D

225

Mr. D: There may be overproduction seen in normal precast for efficiency. But for PPVC, overproduction will be a big mistake. Imagine the entire big PPVC module being produced and left idle at the yard, leaving lesser space for other works. The workers should have done other works first instead of working on this module. This will impact the construction schedule as the modules needs to be installed in sequence. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. D: This depends on the project manager. Project managers who are very experienced and capable would be able to foresee problems and make effort to bring everybody together and remove wastes. The adoption of BIM will also help. I think contractors should have their own BIM coordinator on-board the project to investigate such issues. Relying on the BIM manager from the consultants is not as effective because consultants themselves typically focus on compliance issues and would not be able to think about constructability problems downstream. 8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. D: Design coordination is very important to implement lean and reduce the man-days. Once casting of the first precast starts, precaster would not make much mistake. For the subcontractor doing the installation, the wastes are minor chipping which requires touching up, etc. which are unavoidable due to the nature of precast construction. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. What is your view? Mr. D: This should be the case which is our responsibility as the main contractor. Stakeholders such as consultants would not be bothered about the number of standardised precast components, how the huge precast got to be delivered and hoisted, etc. which will affect the man-days used. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster. Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding?

226

Appendix H: Verbatim Report With Mr. D

Mr. D: I think it depends on the project type. For public residential, the design is quite fixed and it is very hard to further enhance the productivity. For private residential, there are opportunities for us to work together and provide our inputs to the consultants to improve the buildability score. We do not just leave it to the consultants to design based on the minimum requirement. Same for constructability, we also discuss with the consultants on what items to do. One suggestion is that buildability and constructability should be considered by all parties even during the URA Planning Permission stage as changes downstream would be counterproductive. In practice, there is often no time and buildability inputs only come in when there is a need to do Building Plan submission to BCA. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces a leading indicator for precast productivity performance which will be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. This is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to benchmark how they can improve their productivity. What is your view on this? Mr. D: Yes, I am curious about this. This is something good but may be hard to measure. Nevertheless, we still aim to improve productivity not just because of regulations. We find that lean and precast have made it easier to coordinate works on-site. For example, safety risks are reduced. Not just lesser man-days by the workers would be required in the project, but our site management team, also spend lesser man-days to manage and monitor the project. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models? Mr. D: Same thing, it is good but may be hard to measure. About your point earlier for Observation 5, I would like to add that the number of manpower deployed may still be the same as the construction industry is diverse and expertise from various trades are required. In fact, the reduction of these man-days due to the removal of construction wastes may result in these man-days being deployed to do more value-adding work which is also trend of the construction industry. J: This is the last question. Thank you for taking time to share your views with me. Mr. D: Thank you. Good luck for your study. End of Transcript.

Appendix I

Verbatim Report With Mr. E

This is an interview transcript with Mr. E (Main Contractor) on the 13 November 2019, 4 pm to 4.45 pm at the interviewee’s site office. The interviewer shall be referred to as “J”. Begin Transcript: J: Hi, I am currently doing a research study on enabling lean using shared mental models for precast construction in Singapore. The scope of my study is about reducing construction wastes to reduce the total man-days utilised and having team members working together throughout the precast construction process to reduce the total man-days. I have done a survey with 32 companies and the objective of this session is to seek your views on the key observations and results gathered from the survey. Mr. E: I have actually taken the lean construction specialist diploma in BCA Academy. Most of the participants were from main contractor which seems to show that lean should be driven by main contractor. I understand that the intake have been dropping over the years. But it is not as easy to implement lean in the construction industry compared to manufacturing. Toyota is able to do it as car parts are more or less similar across different car models. The process flow is also quite standardised unlike construction sequence which varies from project to project. 1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. E: This is an important point in general but every project is different. Each project has its own constraints and by implementing the same attribute in one © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

227

228

Appendix I: Verbatim Report With Mr. E

project to remove 20% wastes does not mean that implementing the same attribute in another project would also result in 20% wastes reduction. 2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment? Mr. E: We also try to do this but for lean as a whole to be sustainable, my opinion is that the industry can explore having a few standardised column, beam sizes, including the reinforcement design, just like M&E equipment with different capacity. Then, the consultant would have to design accordingly. In this way, precaster can really do mass production. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. E: This is challenging. Contractors must be willing to invest in resources to practice lean through the adoption of lean tools. Even for productive technologies such as BIM, ICT, etc., the rate of usage is very slow in the construction sector. People come from all walks of life, different educational background, many senior people who are very experienced and knowledgeable but their speed of picking up such new technologies and lean approaches may be much slower. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-days utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-days if avoided. Do you agree? Mr. E: We have started practicing lean, doing value stream mapping right from the design stage to remove wastes. Every project would need to re-think and customised its own value stream mapping based on the design, complexity, size, etc. This is a tedious and time-consuming process, especially if you are doing it for the first time. For example, residential project A versus residential project B would still be different. The floor plate is different, components that can be prefabricated and things like the column sizes are also different. All these will affect the man-days required. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’ which may be initiated by the client or consultants due to coordination issues with the various disciplines which should have been initiated earlier.

Appendix I: Verbatim Report With Mr. E

229

Mr. E: My opinion is that design changes should not be considered wastes if the changes are initiated by the client. This is unavoidable in practice as there are reasons why they requested for the changes, usually it is to better meet their operational needs. You cannot expect them to not change if they are willing to pay for the cost and time required. Such changes are constant, even if it is not initiated by the client, as somehow, people bound to make mistakes, major ones are rare. 6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. E: This is an error, wrong arrangement of work leading to inventory and fats. Though we have done value stream mapping to work out the sequence, somehow, there are communication issues which resulted in this scenario as you have seen just beside our site office. I guess the study on the required production and installation sequence was not properly cascaded down to the subcontractor, supervisors and workers. End up, we now have lesser working space to continue with the production. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. E: This should be quite natural if lean is really being practiced. First, we have to price competitively to win the tender. Thereafter, depending on the resources allocated to the project by the company which is also dependent on the price awarded and the contract schedule, the project manager will then be able to get his people to take time and implement lean, if resources are available. Overall, I still feel that lean construction is doable. 8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. E: If you just look at the man-days used to complete ten columns, for example, there will definitely be reduction if construction wastes are removed. Processes should be improved so that man-days can be optimised. If you look at the actual number of workers deployed to do the job, there may not be reduction. For example, a lifting activity would require certain fixed personnel—like the rigger, signalman, etc. If a particular step in the lifting process can be removed, the job can be completed faster but the number of workers will still be the same. If workers

230

Appendix I: Verbatim Report With Mr. E

are multi-skilled to perform other roles, they may be able to do other activities while waiting for the next lifting to be done. But this is not seen today. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. Do you think so too? Mr. E: Yes, like what I said earlier, there would be a cascading effect if the team do not work well together and not passed down the required information promptly, there would be fats and unnecessary man-days incurred. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster. Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding? Mr. E: This is quite unexpected. Because in practice, team members typically only take care of their own areas and would not have time to be aware of and understand the issues in the actual activities. They may not know where the wastes can be cut and which work activities have potential for man-days to be optimised. For example, only the structural personnel would consider how the precast construction activities are going to be done, your formwork, casting, rebar tying, etc. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces a leading indicator for precast productivity performance which will be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. This is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to benchmark how they can improve their productivity. What is your view on this? Mr. E: There are a few parts to this. Although the way BCA used m2 per manday is too generic, it is still relevant and the easiest way to track and have a sensing of the construction productivity. I understand that the industry also used another measure—value-added productivity but this is affected by prices. For example, in a period of economic downturn and contractors dive, the value-added productivity would be reported as very low. But does this mean that contractors are not as productive as before? No. I do agree that we need to have some means to track where we are as the project progresses, even for different disciplines and trades. BCA also does the productivity comparison based on the type of project like industrial, residential, institutional, etc. But this is not very accurate. For example, a data centre project which is M&E heavy compared to a factory

Appendix I: Verbatim Report With Mr. E

231

project, both are categorised as industrial but the productivity is very different. Using floor area is not very accurate. The amount of M&E works in a data centre project is going to be much higher compared to a factory and this will greatly impact the site productivity rate. Next, your idea is a qualitative indicator which is in the right direction as a quantitative indicator would be hard to implement. Contractors can score certain points for adopting a trade productivity monitoring system for the whole project duration under the Constructability score. But how many contractors are scoring on this? I doubt none or very few as it is just too time-consuming and not worth the effort. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models? Mr. E: When you look at the outcome of two exact same buildings, it is likely to be the same. I think that the process of achieving this outcome is also very important which is what your idea is about. J: This is the last question. Thank you for taking time to share your experience and opinions with me. Mr. E: I hope I have answered your questions. Thank you. End of Transcript.

Appendix J

Verbatim Report With Mr. F

This is an interview transcript with Mr. F (Precaster) on the 20 November 2019, 9.45 am to 10.25 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: Hi, I am currently doing a research study on enabling lean using shared mental models for precast construction in Singapore. The scope of my study is about reducing construction wastes to reduce the total man-days utilised and having team members working together throughout the precast construction process to reduce the total man-days. I have done a survey with 32 companies and the objective of this session is to seek your views on the key observations and results gathered from the survey. Mr. F: Ok, I know what you mean, go on. 1. Validating the results of Observation 1a as listed in Appendix D J: Reference to the survey results, the top three attributes were generally rated to result in between 20 and 40% reduction in the occurrence of construction wastes during the precast construction process. First, it is ‘Create continuous process flow to bring problems to the surface’ which means if some problem occurs then the whole process is forced to stop. What is your comments on this? Mr. F: It is what happens after this. Basically, everybody needs to sit down, talk and resolve the problem. If this is done, yes, construction wastes should reduce. 2. Validating the results of Observation 1b as listed in Appendix D J: The second highest attribute is ‘Build a culture of stopping to fix problems, to get quality right the first time’ which means if any problem is discovered, we should stop the work immediately till it is resolved to prevent the same problem from occurring again, especially in mass production. What is your comment?

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

233

234

Appendix J: Verbatim Report With Mr. F

Mr. F: Wear and tear is common in precast. After the mould have been reused many times, it may run a little and the dimensions will be out. We have critical points in place to identify these and will make the improvements immediately to ensure the quality of the next element being produced. For the first few production, the architect, RTO, client’s representatives, main contractor, etc. will go down to our factory to inspect to ensure quality is right the first time. 3. Validating the results of Observation 1c as listed in Appendix D J: How about ‘Focus on long-term results’ rather than looking at short-term gains to result in reduction in construction wastes? Mr. F: To the main contractor, focusing on long-term results is good for them to remove construction wastes. But for us as a precaster, if we are told to expedite or slow down based on the big picture, for example, it will affect our production line deployment which have been planned upfront. As such, we may not be able to accommodate and have to deliver the precast elements to site as per the agreed schedule and the site will have to create a storage space for these precast elements as they are not yet ready to do the installation. 4. Validating the results of Observation 2a as listed in Appendix D J: Next is about reduction in the total man-days utilised, both on-site and off-site. The top attribute is ‘Minimisation of defects and rework due to incompatibility of design with downstream precast construction processes’ which was rated to result in about 10–20% less man-days if avoided. Do you agree? Mr. F: There are just too many different sizes of beams and columns which makes our production not very productive. Nowadays, even for HDB projects where the design is supposedly quite standardised, the man-effort put in is not optimal. I guess it is due to the changing needs where aesthetic is required as you do not want every building to look about the same. Another example is PBU. In the past, after we install the PBU, we do cast in-situ beam before installing the next PBU. Today, we have to do structural PBU which means that more man-effort is required as it is more complex to cast the beam together with the PBU in the factory. The components are bigger, heavier and harder to manage. 5. Validating the results of Observation 2b as listed in Appendix D J: The second highest attribute resulting in lesser man-days used is ‘Minimisation of extra-processing due to design changes’ which may be initiated by the client or consultants due to coordination issues with the various disciplines which should have been initiated earlier. Mr. F: Design changes will always be there. When I attended one of the industry seminar last year, I have heard of the industry asking everybody—contractors, consultants, etc. to come together to standardise precast elements such as walls, refuse chutes, beams, etc. so that off-site construction will be more productive with lesser man-days being utilised. If this is achieved, extra-processing should be minimised as there are standardised components even with design changes.

Appendix J: Verbatim Report With Mr. F

235

6. Validating the results of Observation 2c as listed in Appendix D J: The third highest attribute resulting in lesser man-days used is ‘Minimisation of overproduction due to poor control of precast quantities resulting in the need for inventory’. Mr. F: This may happen if for example, the element being produced is not required to be delivered to site yet based on the agreed schedule. We do make markings to deal with the production process but sometimes, miscommunication still happens. To add on, just-in-time delivery is very hard to achieve, meaning that the element would be ready to be installed the moment it is being delivered to site. If delivery is late due to traffic jam, the workers on-site will need to wait. If the site is congested and not ready to unload the precast elements, the driver will need to wait before they can go back to Malaysia. 7. Validating the results of Observation 3 as listed in Appendix D J: Another observation gathered from the survey is that when reduction of construction wastes due to the implementation of lean construction principles is seen, reduction of construction wastes due to the development of shared mental models will also be seen. What is your views on this? Mr. F: Lean construction is unlike cars. Every seven years, the production line for the specific car models will be re-tooled, and there will be manpower savings. In construction, every project is different. We need to shift out the old moulds to create space for new moulds, dismantle and set up the new mould. Even if we re-use the moulds, they have to be modified which again means manpower is required. Ours is not really mass production like cars. So, there is a limit to how much wastes can be removed. 8. Validating the results of Observation 4 as listed in Appendix D J: Next, when reduction of construction wastes due to the implementation of lean construction principles is observed, reduction in the total man-days used will also be observed. What is your view? Mr. F: By nature, precast is still very labour-intensive. I think the total man-days would not reduce significantly unless precision engineering is adopted which would be much more costly. 9. Validating the results of Observation 5 as listed in Appendix D J: Next, when reduction of construction wastes due to the development of shared mental models among the team members is observed, reduction in the total mandays used will also be observed. Do you think so too? Mr. F: Again, yes but may not be substantial as precast work is labour-intensive. 10. Validating the results of Observation 6 as listed in Appendix D J: The survey was done by members of a different role—Project Manager, Site Structural Engineer, Architectural Coordinator, M&E Coordinator and precaster.

236

Appendix J: Verbatim Report With Mr. F

Generally, the responses obtained from the various roles were rather consistent. What do you think about this finding? Mr. F: On average, I think such an outcome should be more or less there. 11. Validating the results of Observation 7a as listed in Appendix D J: My study also introduces a leading indicator for precast productivity performance which will be predicted based on the extent of reduction in construction wastes due to the implementation of lean principles. This is distinct from the present site productivity measurement which focuses only on on-site manpower and is a lagging indicator which means that the current overall m2 per man-day figure, though tracked monthly, is only known at the end of the project which will be too late for contractors to benchmark how they can improve their productivity. What is your view on this? Mr. F: For us, we track the m3 per man-day for our own benchmarking though it is not a requirement. The figures have been quite standard if we compare the same type of precast elements. For simpler 2D precast elements, the productivity is better. For 3D precast elements such as PBU, the productivity drops. Ours is also a lagging indicator. I would not know if a leading indicator would help significantly as I am only a supplier. 12. Validating the results of Observation 7b as listed in Appendix D J: How about a leading indicator for precast productivity performance predicted based on the extent of reduction of construction wastes due to the development of shared mental models? Mr. F: If there is some way to assess this, it may be useful. But generally, after the first few pieces, the rest should be faster. Based on the precast floor by floor cycle, I think the schedule of architectural and M&E works should follow suit for the entire project to be more productive. So, I am not sure if the leading indicator would be reflective if it is done too early. J: This is the last question. Thank you for taking time to share your experience and opinions with me. Mr. F: Good luck in your study. End of Transcript.

Appendix K

Verbatim Report For Case Study

This is an interview transcript with Mr. G (Main Contractor) on the 23 September 2019, 9.30 am to 10.15 am at the interviewee’s office. The interviewer shall be referred to as “J”. Begin Transcript: J: Hi, thank you for participating in the survey and sharing the productivity data for two of your recently completed projects. As introduced in my survey, I am currently doing a research study on enabling lean using shared mental models for precast construction in Singapore. One deliverable is to develop a leading indicator of precast productivity performance. This is to be used as a benchmark for contractors to monitor their man-day utilisation, both on-site and off-site. The purpose of this interview is to seek your views on the relevance of these 24 inputs, consisting of fourteen lean principles and ten shared mental models attributes, used to construct the leading indicator to predict if the project’s performance would be at high risk or low risk of low precast productivity performance. Mr. G: Are you asking in general or with respect to our two recently completed projects? Also, based on what I can recall, our experience or issues encountered in these two projects are similar which is typical for most of our precast construction projects. J: I am asking in relation to your experience in these two recently completed projects. Based on your survey responses, the model generated showed that the productivity performance of both projects are at high risk of low precast productivity. What is your comment on this? Mr. G: The obvious reason would be because off-site manpower was not accounted in the project productivity figure. Nevertheless, I think it also has to do with the way we manage our projects which can be inferred from our responses. Just take our m2 per man-day figures with some reservations as construction wastes were still seen in both our projects which I think could be further reduced. But it just did not happen as it is not so easy to transform our processes to be lean and to develop shared mental models. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

237

238

Appendix K: Verbatim Report For Case Study

J: Since you pointed out off-site manpower, which key statements in Question Four of the survey do you think are important to result in the scenarios during the production and logistics stages as listed in Question Five of the survey so that the model classifies these two projects as low risk of low precast productivity performance? Mr. G: Ok, for example, “use visual control throughout the process so no problems are hidden”. With this, problems could be easily identified whether it is for works in the factory or on-site. However, I got to know that our precaster’s fabrication sequence did not tally with our site construction schedule due to miscommunication and oversight by whoever was in-charge when the wrong precast components were delivered to site. On goodwill and in instances where the site permits, we tend to give in and find somewhere to store these precast components. The precaster would also have to make some changes in their production schedule and try their best to quickly deliver the correct precast components. J: How about “use pull systems to avoid overproduction” which you have gave a high rating? Mr. G: I believed this is referring to Just-In-Time which we strive to achieve. However, many a times, there were delay in the site activities and we had to ask the precaster to delay the delivery of the precast components. It could be due to wet weather which slowed down the site works or our installation subcontractor who did not allocate sufficient resources to complete the required works. Most of the time, the precaster was able to accommodate if sufficient notice period was given to them. I know this would affect the precaster’s planned production process and timeline but there we simply have no choice. J: Can you elaborate on one more key statement which should significantly reduce the occurrence of construction wastes to result in manpower reduction? Mr. G: Maybe “adapt operations to suit technology, people and processes” which we have also gave a high rating. To share with you, there were occasional lastminute events such as traffic jams and prolonged custom clearance during the transportation of the precast elements from the factory in Malaysia to our construction site. This was not anticipated and I have asked my installation subcontractor workers to report on site early in the morning. While waiting for such delays, the workers were resting as they can only perform specific type of work. If workers in the construction industry are adaptable to do other trade works, they could be deployed to do other tasks. However, sometimes, there could be contractual issues as different subcontractors may be engaged for different type of works. J: How about the shared mental models attributes to reduce construction wastes and consequently reduce the total man-days utilisation? Mr. G: I think this statement “team members have a common goal and form compatible expectations to act accordingly” is important. Precast work is one of the first major activity to be done at the early stage and team members would still have been in the process of developing the standardised procedures to follow. Time was required for them to institutionalise a coordination process and getting commitment from the various team members so that problems could be identified early such as clashes between structural components and M&E services to avoid

Appendix K: Verbatim Report For Case Study

239

the need for design changes and rework if the precast components have been fabricated. J: You also gave a high rating for “team members integrate information and determine the consequences”? Mr. G: This is important because many different disciplines with many people making detailed engineering decisions must fit together at the right time and have to be properly coordinated to deliver the project with minimal construction wastes. J: Which attribute do you think you should have been done but was not executed? Mr. G: “Go and see for yourself to thoroughly understand the situation”. I did not personally go to the factory for the quality inspections due to my tight schedule. I left it to the architect and the residential technical officer to do the checks. This is a slight lapse in a proper quality management process. J: What is your comment on the proposed methodology to predict the leading indicator of precast productivity performance? Mr. G: The attributes are all closely related to productivity outcomes and hence is a good starting point for contractors to use this approach to bring out better productivity performance, rather than not actively doing anything. J: Thank you for taking time to share your views with me. Mr. G: Thank you for sharing your study with us too. All the best to you. End of Transcript.

References

1. Abdul-Rahman H, Wang C, Wood LC, Low SF (2012) Negative impact induced by foreign workers: Evidence in Malaysian construction sector. Habitat International 36(4):433–443 2. Achanga P, Shehab E, Roy R, Nelder G (2006) Critical success factors for lean implementation within SMEs. Journal of Manufacturing Technology Management 17(4):460–471 3. Adler PS (1995) Interdepartmental interdependence and coordination: The case of the Design/Manufacturing interface. Organization Science 6(2):147–167 4. Alagaraja M (2014) A conceptual model of organizations as learning-performance systems: Integrative review of lean implementation literature. Human Resource Development Review 13(2):207–233 5. Al-Ashaab A, Golob M, Attia UM, Khan M, Parsons J, Andino A, Martinez G (2013) The transformation of product development process into lean environment using set-based concurrent engineering: A case study from an aerospace industry. Concurrent Engineering 21(4):268–285 6. Al-Tahat MD, Jalham IS (2015) A structural equation model and a statistical investigation of lean-based quality and productivity improvement. Journal of Intelligent Manufacturing 26(3):571–583 7. Amitha, P., & Priya, T. S. (2017). Waste management process for non-value adding activities using lean construction. Imperial Journal of Interdisciplinary Research, 3(3). 8. Andres HP (2012) Technology-mediated collaboration, shared mental model and task performance. Journal of Organizational and End User Computing (JOEUC) 24(1):64–81 9. Andrews AP, Simon J, Tian F, Zhao J (2011) The Toyota crisis: An economic, operational and strategic analysis of the massive recall. Management Research Review 34(10):1064–1077 10. Anseel F, Lievens F, Schollaert E, Choragwicka B (2010) Response rates in organizational science, 1995–2008: A meta-analytic review and guidelines for survey researchers. Journal of Business and Psychology 25(3):335–349 11. Arayici Y, Coates P, Koskela L, Kagioglou M, Usher C, O’Reilly K (2011) Technology adoption in the BIM implementation for lean architectural practice. Automation in Construction 20(2):189–195 12. Arbulu R, Tommelein I, Walsh K, Hershauer J (2003) Value stream analysis of a re-engineered construction supply chain. Building Research & Information 31(2):161–171 13. Babalola O, Ibem EO, Ezema IC (2019) Implementation of lean practices in the construction industry: A systematic review. Building and Environment 148:34–43 14. Bajjou MS, Chafi A (2018) Lean construction implementation in the Moroccan construction industry. Journal of Engineering, Design and Technology 16(4):533–556

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 J. Ong and L. Sui Pheng, Waste Reduction in Precast Construction, Management in the Built Environment, https://doi.org/10.1007/978-981-15-8799-3

241

242

References

15. Ballard G, Howell G (2003) Lean project management. Building Research & Information 31(2):119–133 16. Bankvall L, Bygballe LE, Dubois A, Jahre M (2010) Interdependence in supply chains and projects in construction. Supply Chain Management: An International Journal 15(5):385–393 17. Baruch Y, Holtom BC (2008) Survey response rate levels and trends in organizational research. Human relations 61(8):1139–1160 18. Beratan, K. K. (2007). A cognition-based view of decision processes in complex social– ecological systems. Ecology and Society, 12(1). 19. Bertelsen S (2004) Lean construction: Where are we and how to proceed. Lean Construction Journal 1(1):46–69 20. Best R, De Valence G (2002) Design and construction: Building and value. ButterworthHeinemann, Boston, MA 21. Black JR (2008) Lean production: Implementing a world-class system, 1st edn. Industrial Press, New York, NY 22. Blunch NJ (2013) Introduction to structural equation modelling using IBM SPSS statistics and AMOS, 2nd edn. SAGE, London 23. Bogue R (2012) Design for manufacture and assembly: Background, capabilities and applications. Assembly Automation 32(2):112–118 24. Building and Construction Authority. (2016). BIM for DfMA essential guide. Retrieved November 9, 2017 from https://www.corenet.gov.sg/media/2032999/bim_essential_guide_ dfma.pdf. 25. Building and Construction Authority. (2017a). Design and build trend. Retrieved April 17, 2017 from https://www.bca.gov.sg/DesignBuild/design_build_statistics_fig1.html. 26. Building and Construction Authority. (2017b). Construction statistics. Retrieved April 23, 2017 from https://www.bca.gov.sg/Infonet/constat.asp. 27. Building and Construction Authority. (2017c). Construction productivity and capability fund. Retrieved April 23, 2017 from https://www.bca.gov.sg/CPCF/cpcf.html. 28. Building and Construction Authority. (2017d). Buildable design legislation. Retrieved June 14, 2017 from http://www.bca.gov.sg/BuildableDesign/legislation2011.html. 29. Building and Construction Authority. (2017e). Code of practice on buildability 2017 edition. Retrieved September 25, 2017 from https://www.bca.gov.sg/BuildableDesign/others/cop 2017.pdf. 30. Building and Construction Authority. (2017f). Prefabricated prefinished volumetric construction guidebook. Retrieved November 9, 2017 from https://www.bca.gov.sg/Professionals/Tec hnology/others/PPVC_Guidebook.pdf. 31. Building and Construction Authority. (2017g). Singapore VDC guide. Retrieved November 9, 2017 from https://www.corenet.gov.sg/media/2094675/singapore-vdc-guide_version1_oct 2017.pdf. 32. Building and Construction Authority. (2018). Integrated construction and prefabrication hub. Retrieved October 24, 2018 from https://www.bca.gov.sg/buildableDesign/tender_pre cast_hub.html. 33. Building and Construction Authority. (2019a). Project productivity. Retrieved April 9, 2019 from https://www.bca.gov.sg/productivity/site_productivity_statistics.html. 34. Building and Construction Authority. (2019b). Prefabricated prefinished volumetric construction. Retrieved April 9, 2019 from https://www.bca.gov.sg/BuildableDesign/ppvc.html. 35. Building and Construction Authority. (2019c). Construction project database. Retrieved July 19, 2019 from https://www.bca.gov.sg/Infonet/database.asp. 36. Cagliano R, Caniato F, Spina G (2006) The linkage between supply chain integration and manufacturing improvement programmes. International Journal of Operations & Production Management 26(3):282–299 37. Canonne C, Aucouturier J (2016) Play together, think alike: Shared mental models in expert music improvisers. Psychology of Music 44(3):544–558 38. Cassidy, S. A., & Stanley, D. J. (2018). Getting from ‘Me’ to ‘We’: Role clarity, team process, and the transition from individual knowledge to shared mental models in employee dyads: From knowledge to shared mental models. Canadian Journal of Administrative Sciences.

References

243

39. Chang LY (2005) Analysis of freeway accident frequencies: Negative binomial regression versus artificial neural network. Safety Science 43(8):541–557 40. Changali, S., Mohammad, A., & Nieuwland, M. V. (2015). The construction productivity imperative. Retrieved May 12, 2017 from http://www.mckinsey.com/industries/capital-pro jects-and-infrastructure/our-insights/the-construction-productivity-imperative. 41. Chen Y, Okudan GE, Riley DR (2010) Sustainable performance criteria for construction method selection in concrete buildings. Automation in Construction 19(2):235–244 42. Cheung SO, Tam CM, Harris FC (2000) Project dispute resolution satisfaction classification through neural network. Journal of Management in Engineering 16(1):70–79 43. Choy E, Ruwanpura JY (2006) Predicting construction productivity using situation-based simulation models. Canadian Journal of Civil Engineering 33(12):1585–1600 44. Converse, S. A., Cannon-Bowers, J. A., & Salas, E. (1991). Team member shared mental models: A theory and some methodological issues. In Proceedings of the Human Factors Society Annual Meeting (Vol. 35, No. 19, pp. 1417–1421). Sage CA: Los Angeles, CA: SAGE Publications. 45. Converse S, Cannon-Bowers JA, Salas E (1993) Shared mental models in expert team decision making. Current Issues, Individual and Group Decision Making, p 221 46. Cortina JM (1993) What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology 78(1):98 47. Dao MA, Strobl A, Bauer F, Tarba SY (2017) Triggering innovation through mergers and acquisitions: The role of shared mental models. Group & Organization Management 42(2):195–236 48. Dave B, Kubler S, Främling K, Koskela L (2016) Opportunities for enhanced lean construction management using Internet of Things standards. Automation in Construction 61:86–97 49. Dave B, Pikas E, Kerosuo H, Mäki T (2015) ViBR–conceptualising a virtual big room through the framework of people, processes and technology. Procedia Economics and Finance 21:586– 593 50. Dhanaraj C, Khanna T (2011) Transforming mental models on emerging markets. Academy of Management Learning & Education 10(4):684–701 51. Dionne SD, Sayama H, Hao C, Bush BJ (2010) The role of leadership in shared mental model convergence and team performance improvement: An agent-based computational model. The Leadership Quarterly 21(6):1035–1049 52. Doran D, Giannakis M (2011) An examination of a modular supply chain: A construction sector perspective. Supply Chain Management: An International Journal 16(4):260–270 53. Dulaimi MF, Ling FYY, Ofori G (2004) Engines for change in Singapore’s construction industry: An industry view of Singapore’s construction 21 report. Building and Environment 39(6):699–711 54. Durdyev S, Ismail S (2016) On-site construction productivity in Malaysian infrastructure projects. Structural Survey 34(4/5):446–462 55. Efron B (1983) Estimating the error rate of a prediction rule: Improvement on cross-validation. Journal of the American Statistical Association 78(382):316–331 56. El-Gohary KM, Aziz RF (2013) Factors influencing construction labor productivity in Egypt. Journal of Management in Engineering 30(1):1–9 57. Espevik R, Johnsen BH, Eid J (2011) Outcomes of shared mental models of team members in cross training and high-intensity simulations. Journal of Cognitive Engineering and Decision Making 5(4):352–377 58. Evans JM, Ross Baker G (2012) Shared mental models of integrated care: Aligning multiple stakeholder perspectives. Journal of Health Organization and Management 26(6):713–736 59. Fawcett T (2006) An introduction to ROC analysis. Pattern Recognition Letters 27(8):861–874 60. Forbes LH, Ahmed SM (2010) Modern construction: Lean project delivery and integrated practices. CRC Press, Boca Raton, FL 61. Fransen J, Kirschner PA, Erkens G (2011) Mediating team effectiveness in the context of collaborative learning: The importance of team and task awareness. Computers in Human Behavior 27(3):1103–1113

244

References

62. Fulford R, Standing C (2014) Construction industry productivity and the potential for collaborative practice. International Journal of Project Management 32(2):315–326 63. Gambatese JA, Lee HW, Pestana C (2017) Alignment between lean principles and practices and worker safety behavior. Journal of Construction Engineering and Management 143(1):4016083 64. Gao S, Low SP (2014) Lean construction management: The Toyota Way. Springer Singapore, Singapore 65. Gao S, Low SP (2015) Implementing Toyota Way principles for construction projects in China: A case study. International Journal of Construction Management 15(3):179–195 66. Gao S, Low SP, Nair K (2018) Design for manufacturing and assembly (DfMA): A preliminary study of factors influencing its adoption in Singapore. Architectural Engineering and Design Management 14(6):440–456 67. Ghosh S, Robson KF (2015) Analyzing the empire state building project from the perspective of lean delivery system—A descriptive case study. International Journal of Construction Education and Research 11(4):257–267 68. Gibb A, Isack F (2003) Re-engineering through pre-assembly: Client expectations and drivers. Building Research & Information 31(2):146–160 69. Gidado K (2004) Enhancing the prime contractor’s pre-construction planning. Journal of Construction Research 5(01):87–106 70. Goh M, Goh YM (2019) Lean production theory-based simulation of modular construction processes. Automation in Construction 101:227–244 71. Goodrum PM, Haas CT, Caldas C, Zhai D, Yeiser J, Homm D (2010) Model to predict the impact of a technology on construction productivity. Journal of Construction Engineering and Management 137(9):678–688 72. Goodrum PM, Zhai D, Yasin MF (2009) Relationship between changes in material technology and construction productivity. Journal of Construction Engineering and Management 135(4):278–287 73. Goodwin, G. F., Burke, C. S., Rosen, M. A., & Salas, E. (2008). The wisdom of collectives in organizations: An update of the teamwork competencies. In Team Effectiveness In Complex Organizations (pp. 73–114). Routledge. 74. Goulding JS, Pour Rahimian F, Arif M, Sharp MD (2015) New offsite production and business models in construction: Priorities for the future research agenda. Architectural Engineering and Design Management 11(3):163–184 75. Green SD (2002) The human resource management implications of lean construction: Critical perspectives and conceptual chasms. Journal of Construction Research 3(01):147–165 76. Greenwood, D. J., Jie, L. T., & Rogage, K. (2017). An investigation into ‘Lean-BIM’ synergies in the UK construction industry. International Journal of 3-D Information Modeling (IJ3DIM), 6(2), 1–13. 77. Gunawardena T, Ngo T, Mendis P, Aye L, Crawford R (2014) Time-efficient post-disaster housing reconstruction with prefabricated modular structures. Open House International 39(3):59–69 78. Gurtner A, Tschan F, Semmer NK, Nägele C (2007) Getting groups to develop good strategies: Effects of reflexivity interventions on team process, team performance, and shared mental models. Organizational Behavior and Human Decision Processes 102(2):127–142 79. Heravi G, Firoozi M (2017) Production process improvement of buildings’ prefabricated steel frames using value stream mapping. The International Journal of Advanced Manufacturing Technology 89(9–12):3307–3321 80. Holweg M (2007) The genealogy of lean production. Journal of Operations Management 25(2):420–437 81. Hook M, Stehn L (2008) Applicability of lean principles and practices in industrialized housing production. Construction Management and Economics 26(10):1091–1100 82. Horman MJ, Thomas HR (2005) Role of inventory buffers in construction labor performance. Journal of Construction Engineering and Management 131(7):834–843

References

245

83. Hosseini MR, Martek I, Chileshe N, Zavadskas EK, Arashpour M (2018) Assessing the influence of virtuality on the effectiveness of engineering project networks: “Big Five Theory” perspective. Journal of Construction Engineering and Management 144(7):04018059 84. Housing and Development Board. (2017). Precast technology. Retrieved October 21, 2017 from http://www.hdb.gov.sg/cs/infoweb/about-us/our-role/smart-and-sustainable-living/inn ovations/precast-technology-page. 85. Hsu JS, Chang JY, Klein G, Jiang JJ (2011) Exploring the impact of team mental models on information utilization and project performance in system development. International Journal of Project Management 29(1):1–12 86. Hughes R, Thorpe D (2014) A review of enabling factors in construction industry productivity in an Australian environment. Construction Innovation 14(2):210–228 87. Hwang BG, Shan M, Looi KY (2018) Key constraints and mitigation strategies for prefabricated prefinished volumetric construction. Journal of cleaner production 183:183–193 88. J.D. Power. (2016). U.S. vehicle dependability study. Retrieved September 4, 2016 from http:// www.jdpower.com/resource/us-vehicle-dependability-study. 89. Jamil AHA, Fathi MS (2016) The integration of lean construction and sustainable construction: A stakeholder perspective in analyzing sustainable lean construction strategies in Malaysia. Procedia Computer Science 100:634–643 90. Johnson-Laird PN (1983) Mental models: Towards a cognitive science of language, inference, and consciousness. Harvard University Press, Cambridge, Mass 91. Jones C, Medlen N, Merlo C, Robertson M, Shepherdson J (1999) The lean enterprise. BT Technology Journal 17(4):15–22 92. Jonker, C. M., Van Riemsdijk, M. B., & Vermeulen, B. (2011). Shared mental models. In Coordination, organizations, institutions, and norms in agent systems vi (pp. 132–151). Berlin, Heidelberg: Springer. 93. Jorgenson DW, Kuroda M, Nishimizu M (1987) Japan-US industry-level productivity comparisons, 1960–1979. Journal of the Japanese and International Economies 1(1):1–30 94. Kazaz A, Acikara T (2015) Comparison of labor productivity perspectives of project managers and craft workers in Turkish construction industry. Procedia Computer Science 64:491–496 95. Kazaz A, Ulubeyli S, Acikara T, Er B (2016) Factors affecting labor productivity: Perspectives of craft workers. Procedia Engineering 164:28–34 96. Kehr TW, Proctor MD (2017) People pillars: Re-structuring the Toyota Production System (TPS) house based on inadequacies revealed during the automotive recall crisis: Re-structuring the TPS house based on the automotive recall crisis. Quality and Reliability Engineering International 33(4):921–930 97. Kenney, M., & Florida, R. L. (1993). Beyond mass production: The Japanese system and its transfer to the U.S. New York: Oxford University Press. 98. Kim P (2017) MATLAB deep learning: With machine learning, neural networks and artificial intelligence. Apress, Berkeley, CA 99. Kim M, Gilley JE (2008) Artificial Neural Network estimation of soil erosion and nutrient concentrations in runoff from land application areas. Computers and Electronics in Agriculture 64(2):268–275 100. Kim D, Park H (2006) Innovative construction management method: Assessment of lean construction implementation. KSCE Journal of Civil Engineering 10(6):381–388 101. Knaack, U., Chung-Klatte, S., & Hasselbach, R. (2009). Prefabricated systems: Principles of construction. Basel; London: Birkhäuser. 102. Koskela L (1992) Application of the new production philosophy to construction, vol 72. Stanford University, Stanford, CA 103. Koskela, L. (2017). Lean construction views, advice, and predictions. Retrieved October 12, 2017 from https://www.irishbuildingmagazine.ie/2017/09/12/lauri-koskelas-lean-constr uction-views-advice-and-predictions/. 104. Krafcik JF (1988) Triumph of the lean production system. MIT Sloan Management Review 30(1):41

246

References

105. Lapinski AR, Horman MJ, Riley DR (2006) Lean processes for sustainable project delivery. Journal of Construction Engineering and Management 132(10):1083–1091 106. Laufer A, Tucker RL (1987) Is construction project planning really doing its job? A critical examination of focus, role and process. Construction Management and Economics 5(3):243– 266 107. Lawson M, Ogden R, Goodier C (2014) Design in modular construction. CRC Press, London 108. Lee JS, Kim YS (2017) Analysis of cost-increasing risk factors in modular construction in Korea using FMEA. KSCE Journal of Civil Engineering 21(6):1999–2010 109. Lee WR, Beruvides MG, Chiu YD (2007) A study on the quality-productivity relationship and its verification in manufacturing industries. The Engineering Economist 52(2):117–139 110. Li H, Guo HL, Li Y, Skitmore M (2012) From IKEA model to the lean construction concept: A solution to implementation. International Journal of Construction Management 12(4):47–63 111. Liker, J. K. (1997). Becoming lean: Inside stories of U.S. manufacturers. Portland, Or: Productivity Press. 112. Liker JK (2004) The Toyota Way: 14 management principles from the world’s greatest manufacturer. McGraw-Hill, New York 113. Liker JK, Convis GL (2012) The Toyota Way to lean leadership: Achieving and sustaining excellence through leadership development. McGraw-Hill, New York 114. Liker JK, Franz JK (2011) The Toyota Way to continuous improvement: Linking strategy with operational excellence to achieve superior performance. McGraw-Hill, New York 115. Liker, J. K., & Meier, D. (2006). The Toyota Way fieldbook: A practical guide for implementing Toyota’s 4Ps. New York;London: McGraw-Hill. 116. Lim BC, Klein KJ (2006) Team mental models and team performance: A field study of the effects of team mental model similarity and accuracy. Journal of Organizational Behavior 27(4):403–418 117. Ling FYY, Kerh SH (2004) Comparing the performance of design-build and design-bid-build building projects in Singapore. Architectural Science Review 47(2):163–175 118. Ling FYY, Dulaimi MF, Chua M (2012) Strategies for managing migrant construction workers from China, India, and the Philippines. Journal of Professional Issues in Engineering Education and Practice 139(1):19–26 119. Locatelli, G., Mancini, M., Gastaldo, G., & Mazza, F. (2013). Improving projects performance with lean construction: State of the art, applicability and impacts. Organization, Technology & Management in Construction: An International Journal, 5(Special), 775–783. 120. Loukas YL (2000) Artificial neural networks in liquid chromatography: Efficient and improved quantitative structure–retention relationship models. Journal of Chromatography A 904(2):119–129 121. Low SP, Gao S, Luen KWP (2016) Using lean principles to reduce wastes in the concreting supply chain. International Journal of Construction Project Management 8(1):3–23 122. Low SP, Tan BK, Ang AL (1999) Effectiveness of ISO 9000 in raising construction quality standards: Some empirical evidence using CONQUAS scores. Structural Survey 17(2):89–108 123. Lu W, Yuan H (2013) Investigating waste reduction potential in the upstream processes of offshore prefabrication construction. Renewable and Sustainable Energy Reviews 28:804–811 124. Mao C, Shen Q, Pan W, Ye K (2015) Major barriers to off-site construction: The developer’s perspective in China. Journal of Management in Engineering 31(3):04014043 125. Marhani MA, Jaapar A, Bari NAA, Zawawi M (2013) Sustainability through lean construction approach: A literature review. Procedia-Social and Behavioral Sciences 101:90–99 126. Marks MA, Zaccaro SJ, Mathieu JE (2000) Performance implications of leader briefings and team-interaction training for team adaptation to novel environments. Journal of Applied Psychology 85(6):971 127. Maturana S, Alarcón LF, Gazmuri P, Vrsalovic M (2007) On-site subcontractor evaluation method based on lean principles and partnering practices. Journal of Management in Engineering 23(2):67–74 128. Maynard MT, Gilson LL (2014) The role of shared mental model development in understanding virtual team effectiveness. Group & Organization Management 39(1):3–32

References

247

129. McComb, S. A. (2007). Mental model convergence: The shift from being an individual to being a team member. In Multi-level issues in organizations and time (pp. 95–147). Emerald Group Publishing Limited. 130. Minami NA, Soto LL, Rhodes DH (2010) Dynamic lean management of the naval construction process. Engineering Management Journal 22(2):36–43 131. Ministry of Manpower. (2019). Foreign workforce numbers. Retrieved April 9, 2019 from https://www.mom.gov.sg/documents-and-publications/foreign-workforce-numbers. 132. Ministry of National Development. (2015). Speech by SMS Lee Yi Shyan at committee of supply debate—bolder steps to boost productivity. Retrieved August 4, 2016 from http://app.mnd.gov.sg/Newsroom/NewsPage.aspx?ID=4292&category=Speech&year= 2013&RA1=&RA2=&RA3. 133. Ministry of Trade and Industry. (2019). Singstats table builder - changes in value added per actual hour worked at 2010 market prices by industry. Retrieved May 2, 2019 from http:// www.tablebuilder.singstat.gov.sg/publicfacing/createDataTable.action?refId=12384. 134. Molloy, O., Warman, E. A., & Tilley, S. (2012). Design for Manufacturing and Assembly: Concepts, architectures and implementation. Springer Science & Business Media. 135. Mostafa S, Mostafa S, Chileshe N, Chileshe N, Abdelhamid T, Abdelhamid T (2016) Lean and agile integration within offsite construction using discrete event simulation: A systematic literature review. Construction Innovation 16(4):483–525 136. Nadim W, Goulding JS (2010) Offsite production in the UK: The way forward? A UK construction industry perspective. Construction innovation 10(2):181–202 137. Nahmens I, Ikuma LH (2011) Effects of lean construction on sustainability of modular homebuilding. Journal of Architectural Engineering 18(2):155–163 138. Nanyang Technological University. (2016). NTU develops smart crane for precast building. Retrieved June 3, 2017 from http://news.ntu.edu.sg/pages/newsdetail.aspx?URL=http:// news.ntu.edu.sg/news/Pages/Media2016_Dec04.aspx&Guid=3531adb7-3537-461f-b326d814893b4fc1&Category=All. 139. Naoum SG (2016) Factors influencing labor productivity on construction sites: A state-ofthe-art literature review and a survey. International Journal of Productivity and Performance Management 65(3):401 140. Nasir H, Ahmed H, Haas C, Goodrum PM (2014) An analysis of construction productivity differences between Canada and the United States. Construction Management and Economics 32(6):595–607 141. Ofori DF (2013) Project management practices and critical success factors—A developing country perspective. International Journal of Business and Management 8(21):14 142. Ofori G, Lim KH (2009) Multi-layered subcontracting system in Singapore’s construction industry. Joint ventures in construction. Thomas Telford Publishing, Great Britain, pp 216–226 143. Oglesby CH, Parker HW, Howell GA (1989) Productivity improvement in construction. Mcgraw-Hill, New York 144. Ogunbiyi O, Goulding JS, Oladapo A (2014) An empirical study of the impact of lean construction techniques on sustainable construction in the UK. Construction Innovation 14(1):88–107 145. Ohno T (1988) Toyota Production System: Beyond large-scale production. Productivity Press, Cambridge, Mass 146. Orr, C. (2005). 13th international group for lean construction conference: proceedings - lean leadership in construction. Retrieved August 1, 2016 from http://search.informit.com.au.lib proxy1.nus.edu.sg/documentSummary;dn=565392600881852;res=IELENG. 147. Pan W, Gibb AG, Dainty AR (2007) Perspectives of UK housebuilders on the use of offsite modern methods of construction. Construction Management and Economics 25(2):183–194 148. Panwar A, Nepal BP, Jain R, Rathore APS (2015) On the adoption of lean manufacturing principles in process industries. Production Planning & Control 26(7):564–587 149. Park S (1996) Beyond lean production?: Cost reduction strategies through globalisation and restructuring in West Europe (Germany): A comparison with Japan. Institute of Social Science, University of Tokyo, Tokyo

248

References

150. Rackauskaite E, Kotsovinos P, Rein G (2017) Structural response of a steel-frame building to horizontal and vertical travelling fires in multiple floors. Fire Safety Journal 91:542–552 151. Rao BP, Jartarghar NS, Ramamurthy N (2014) A study on the perceptions of clients, contractors and consultants towards precast construction technology. International Journal of Emerging Technology and Advanced Engineering 4(5):291–300 152. Rausch C, Nahangi M, Perreault M, Haas CT, West J (2016) Optimum assembly planning for modular construction components. Journal of Computing in Civil Engineering 31(1):04016039 153. Ray B, Ripley P, Neal D (2006) Lean manufacturing—A systematic approach to improving productivity in the precast concrete industry. PCI journal 51(1):62–71 154. Rebano-Edwards S (2007) Modelling perceptions of building quality—A neural network approach. Building and Environment 42(7):2762–2777 155. Rinehart JW, Huxley CV, Robertson D (1997) Just another car factory?: Lean production and its discontents. ILR Press, Ithaca, NY 156. Rojas EM, Aramvareekul P (2003) Labor productivity drivers and opportunities in the construction industry. Journal of Management in Engineering 19(2):78–82 157. Romano P (2003) Coordination and integration mechanisms to manage logistics processes across supply networks. Journal of Purchasing and Supply Management 9(3):119–134 158. Rother, M., & Shook, J. (1999). Learning to see: Value stream mapping to add value and eliminate muda (Version 1.2. ed.). Brookline, Mass: Lean Enterprise Institute. 159. Rouse WB, Cannon-Bowers JA, Salas E (1992) The role of mental models in team performance in complex systems. IEEE Transactions on Systems, Man, and Cybernetics 22(6):1296–1308 160. Ruona WE, Lynham SA (2004) A philosophical framework for thought and practice in human resource development. Human Resource Development International 7(2):151–164 161. Russell JS, Stouffer B (2003) Leadership: Is it time for an educational change? Leadership and Management in Engineering 3(1):2–3 162. Salas E, Fiore SM (2004) Team cognition: Understanding the factors that drive process and performance, 1st edn. American Psychological Association, Washington, DC 163. Salem O, Solomon J, Genaidy A, Luegring M (2005) Site implementation and assessment of lean construction techniques. Lean Construction Journal 2(2):1–21 164. Samarasinghe, S. (2016). Neural networks for applied sciences and engineering: From fundamentals to complex pattern recognition. CRC Press. 165. Santorella, G. (2016). Lean culture for the construction industry: Building responsible and committed project teams. CRC Press. 166. Schalkoff R (1997) Artificial neural networks. The McGraw-Hill Companies Inc, New York 167. Scheutz M, DeLoach SA, Adams JA (2017) A framework for developing and using shared mental models in human-agent teams. Journal of Cognitive Engineering and Decision Making 11(3):203–224 168. Schmidtke JM, Cummings A (2017) The effects of virtualness on teamwork behavioral components: The role of shared mental models. Human Resource Management Review 27(4):660–677 169. Selladurai R (2002) An organizational profitability, productivity, performance (PPP) model: Going beyond TQM and BPR. Total Quality Management 13(5):613–619 170. Shen L, Zhou J (2014) Examining the effectiveness of indicators for guiding sustainable urbanization in China. Habitat International 44:111–120 171. Sinclair, B. R., Mousazadeh, S., & Safarzadeh, G. (2012). Agility, adaptability + appropriateness: Conceiving, crafting & constructing an architecture of the 21st century. Enquiry: A Journal for Architectural Research, 9(1). 172. Singapore. National Productivity Board. Research and Information Centre (1993) Lean production. National Productivity Board, Singapore 173. Smith-Jentsch KA, Cannon-Bowers JA, Tannenbaum SI, Salas E (2008) Guided team selfcorrection: Impacts on team mental models, processes, and effectiveness. Small Group Research 39(3):303–327

References

249

174. Soekiman A, Pribadi KS, Soemardi BW, Wirahadikusumah RD (2011) Factors relating to labor productivity affecting the project schedule performance in Indonesia. Procedia Engineering 14:865–873 175. Song L, Liang D (2011) Lean construction implementation and its implication on sustainability: A contractor’s case study. Canadian Journal of Civil Engineering 38(3):350–359 176. Spear S, Bowen HK (1999) Decoding the DNA of the Toyota Production System. Harvard Business Review 77:96–108 177. Staib, G., Dörrhöfer, A., & Rosenthal, M. (2013). Components and systems: Modular construction—Design, structure, new technologies. Walter de Gruyter. 178. Stout RJ, Cannon-Bowers JA, Salas E, Milanovich DM (1999) Planning, shared mental models, and coordinated performance: An empirical link is established. Human Factors 41(1):61–71 179. Stoyanova N, Kommers P (2002) Concept mapping as a medium of shared cognition in computer-supported collaborative problem solving. Journal of Interactive Learning Research 13(1):111–133 180. Tam VW, Tam CM, Ng WC (2007) On prefabrication implementation for different project types and procurement methods in Hong Kong. Journal of Engineering, Design and Technology 5(1):68–80 181. Tan W (2000) Total factor productivity in Singapore construction. Engineering Construction and Architectural Management 7(2):154–158 182. Teo, E. A. L., Ofori, G., Tjandra, I. K., & Kim, H. (2015). The potential of Building Information Modelling (BIM) for improving productivity in Singapore construction. In Proceedings of the 31st Annual ARCOM Conference, Lincoln, UK, 7–9 September (pp. 661-670). Association of Researchers in Construction Management, London, UK. 183. Terry A, Smith S (2011) Build lean: Transforming construction using lean thinking. CIRIA, London 184. Thomas HR, Horman MJ, de Souza UEL, Zavˇrski I (2002) Reducing variability to improve performance as a lean construction principle. Journal of Construction Engineering and management 128(2):144–154 185. Thomas HR, Horman MJ, Minchin RE Jr, Chen D (2003) Improving labor flow reliability for better productivity as lean construction principle. Journal of Construction Engineering and Management 129(3):251–261 186. Torres, N., & Olaya, C. (2010, July). Tackling the mess: System conceptualization through cross-impact analysis. In Proceeding of the 28th International Conference of the System Dynamics Society, Seoul, Korea (pp. 25–29). 187. Van den Bossche P, Gijselaers W, Segers M, Woltjer G, Kirschner P (2011) Team learning: Building shared mental models. Instructional Science 39(3):283–301 188. Volpe CE, Cannon-Bowers JA, Salas E, Spector PE (1996) The impact of cross-training on team functioning: An empirical investigation. Human Factors 38(1):87–100 189. Vrijhoef R, Koskela L (2000) The four roles of supply chain management in construction. European Journal of Purchasing and Supply Management 6(3):169–178 190. Wang L, Buchanan TS (2002) Prediction of joint moments using a neural network model of muscle activations from EMG signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering 10(1):30–37 191. Warner, N., Letsky, M., & Cowen, M. (2005, September). Cognitive model of team collaboration: Macro-cognitive focus. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 49, No. 3, pp. 269–273). CA: Los Angeles, CA: SAGE Publications. 192. Williams DK, Kovach AL, Muddiman DC, Hanck KW (2009) Utilizing artificial neural networks in MATLAB to achieve parts-per-billion mass measurement accuracy with a fourier transform ion cyclotron resonance mass spectrometer. Journal of the American Society for Mass Spectrometry 20(7):1303–1310 193. Womack, J. P., & Jones, D. T. (2003). Lean thinking: Banish waste and create wealth in your corporation (1st Free Press, rev. and updated.). New York: Free Press.

250

References

194. Womack, J. P., Jones, D. T., Roos, D., & Massachusetts Institute of Technology. (1990). The machine that changed the world: Based on the Massachusetts Institute of Technology 5-million dollar 5-year study on the future of the automobile. New York: Rawson Associates. 195. Worley JM, Doolen TL (2015) Organizational structure, employee problem solving, and lean implementation. International Journal of Lean Six Sigma 6(1):39–58 196. Yang HD, Kang HR, Mason RM (2008) An exploratory study on meta skills in software development teams: Antecedent cooperation skills and personality for shared mental models. European Journal of Information Systems 17(1):47–61 197. Yi W, Chan AP (2013) Critical review of labor productivity research in construction journals. Journal of Management in Engineering 30(2):214–225 198. Yin SY, Tserng HP, Toong SN, Ngo TL (2014) An improved approach to the subcontracting procurement process in a lean construction setting. Journal of Civil Engineering and Management 20(3):389–403 199. Yu X, Petter S (2014) Understanding agile software development practices using shared mental models theory. Information and Software Technology 56(8):911–921 200. Zhang Y (2012) The impact of task complexity on people’s mental models of MedlinePlus. Information Processing & Management 48(1):107–119