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PERFORMANCE IMPROVEMENT IN APPAREL 
MANUFACTURING USING LEAN TECHNIQUES
LIBRARY
UNIVERSITY OF MORATUWA. SRI LANKa
MORATUWA
by
R.M.V.S. RATNAYAKE
This thesis was submitted to the 
Department of Textile & Clothing Technology 
of the University ofMoratiiwa 
In partial fulfillment of the requirements of the 
Degree of
\
Master of Philosophyii
■
?
University of Moratuwai
; 93885
Department of Textile & Clothing Technology 
University of Moratuwa 
October 2009 9388S
CCD'' 'CO h)lorJh
bll W
Ill- C>5 (MS)
n n rJjooj
Declaration:
I hereby certify that the work incorporated in this thesis was solely carried out by me 
under the supervision of Dr. HSC Perera and Dr. WDG Lanarolle. No portion of work in 
this thesis or any material incorporated in it has not been submitted for any University or 
Institution for any other academic qualification.
RMVS Ratnayake 
(Candidate)
Dr. HSC Perera 
(Supervisor)
Dr. WDG Lanarolle
(Supervisor)
i
i
Abstract
The labour productivity in the Sri Lankan garment industry is found to be rather low 
compared to that of some of its competitive countries. On site investigation revealed that 
the workflow gets unbalanced due to many reasons despite it is balanced at the 
commencement of a new style. The Work In Progress (WIP) and its fluctuation arc 
found as two apparent factors reducing the labour productivity in addition to disorganized 
set-up activities during style changes. The significance of the problem of high WIP and 
its high fluctuation are investigated through the data collected from 42 garment 
manufacturing lines in 14 different factories. Hypothesis testing on these data revealed 
that this is a common problem across all 14 factories under this study. Root cause 
analysis on WIP fluctuation disclosed the major contributing factors to the problem. 
Identifying each sewing line in few ‘sub-cells', where a team of operators focuses mainly 
on one part of the garment helped addressing most of the problems identified in the root 
cause analysis. An algorithm to balance the production line and the sub-cells is devised. 
The concept was successfully implemented in a garment manufacturing company in Sri 
Lanka. The evaluation of the performance indicators revealed that the production 
efficiency has increased by more than 10% while drastically reducing the defect 
percentage. The operator absenteeism too has significantly reduced. This may be due to 
the fact that the operators’ motivation to work and their income are increased as disclosed 
by the results of the questionnaire survey among operators and the supervisors.
High, but inevitable, style changes aggravate the problem of low labour productivity as 
drastic production efficiency drops are experienced during the changeover. The quick 
changeovers concepts commonly found in lean manufacturing and newly proposed five- 
step set-up procedure streamlined the set-up activities. The implementation of the 
proposed set-up procedure made it possible to increase the average first day production 
efficiency of the factory over 80% and a significant reduction in the set-up times as 
compared with the statistics before implementation.
u
Acknowledgements
I owe my deepest gratitude to the supervisors of my research Dr.Chandana Perera and 
Dr.Gamini Lanarolle, who guided me in the correct pathway in achieving the objectives of this 
research. Their patience in reading and correcting the thesis is highly appreciated.
I wish to pay my tribute for the efforts taken by the members of the progress review committee, 
Dr.Julian Nanayakkara, Dr. Udaya Kahangamage, Mr.Raj Prasanna and Dr.Sanath 
Jayawardena towards the successful completion of my research work, 
proficiency and the experience of Dr.Julian Nanayakkara as the Chairman of the committee 
towards the latter part of the research helped me immensely in presenting this research more 
scientifically.
The unmatched
I wish to thank Prof. Terrence Perera of Sheffield Hallam University and Dr.Nirmali de Silva 
of the Department of Textile & Clothing Technology in forming a link between the two 
institutions and to thank the British Council, Colombo, for funding this educational link. My 
visit to Sheffield Hallam University funded by this link helped me in collecting a huge amount 
of research materials, and to develop links with professionals in the field of lean manufacturing. 
Mr.James Marsh is one such academic who advised and helped me where needed, and I wish to 
offer my sincere thanks to him.
Special thanks are due to Mr.J.N. Gunasena and Mr.Ruwan Malaka of Hirdaramani Industries 
Pvt. Ltd at Kahathuduwa; without their commitment, the implementation of the research would 
not have been possible. I also express my gratitude to the staff of the garment manufacturing 
companies who assisted me in collecting data and filling questionnaires and by providing 
necessary information.
I wish to thank the University of Moratuwa for giving me this opportunity for doing this 
postgraduate research. I am grateful to Ms Samanthi Mathugama and Ms.Padma Yatapana of 
the Mathematics Department for the assistance given in statistical analysis of the data. The 
continuous support and the encouragement of the Heads of Department of Textile & Clothing 
Technology during my research period and the staff, specially Mr.Ranga Abeysooriya are 
remembered and I wish to express my gratitude to all of them.
Finally, I wish to thank my beloved mother, husband and two sons, 
encouragement and patience 1 would not have been able to complete this research.
Without their
iii
Table of Contents
Page
Declaration
Abstract
Acknowledgement 
Table of Contents 
List of Figures 
List of Tables 
Abbreviations
i
ii
in
IV
viii
x
XIV
1. Introduction
11.1 Background
1Textile & Garment Industry in Sri Lanka 
Main concerns for remaining competitive
1.2 Lean manufacturing as a performance improvement tool
1.3 Statement of the problem
1.4 Objectives
1.5 Significance of the research
1.6 Outline of the research
1.1.1
1.1.2
5
6
6
7
7
2. Literature Review
2.1 Introduction
2.2 Lean Manufacturing
2.2.1 The development of Toyota Production System and Lean 
Manufacturing
2.2.2 Lean Principles - the five phase implementation model
2.2.3 Eight wastes in manufacturing
2.3 Lean manufacturing tools and techniques
2.3.1 Value Stream Mapping
2.3.2 Just In Time (JIT) philosophy
2.3.3 Group Technology and Cellular Manufacturing
2.3.4 Set-up time reduction
2.3.5 Total Productive Maintenance (TPM)
2.3.6. Total Quality Management (TQM)
2.3.7 Kanban systems
2.3.8 Work Standardization
2.3.9 Visual controls and audio signals
2.3.10 The principles of 5S
2.3.11 Poka-yoke
9
9
10
11
12
14
14
20
21
25
29
34
37
38
39
40
42
IV
422.3.12 Jidoka
2.3.13 Heijinika
2.3.14 Kaizen
2.4 Simulation in lean implementation
2.5 Benefits of Lean Implementation 
Problems in lean implementation
2.7 Summary and Discussion
42
42
43
44
452.6
46
3. Scope of the Study
3.1 Introduction
3.2 Productivity
3.3 Lead time
3.4 Reliability
3.5 Flexibility
3.6 Supply chain
3.7 Garment manufacturing process
3.8 Summary of scope and limitations
48
48
50
52
53
53
54
59
4. Methodology
4.1 Introduction
4.2 Literature survey
4.3 A survey on wastes in garment manufacturing lines
4.4 Identifying operations and wastes in garment manufacturing
4.5 Cellular manufacturing model
4.6 Implementation of the system
61
62
62
62
63
64
5. Analysis of the current state of a production line in a 
selected garment factory
5.1 Introduction
5.2 Layouts of garment manufacturing lines
5.3 Investigation of the current practice
5.3.1 Reveals of the study
5.4 Is the problem of WIP fluctuation common to other production 
lines?
5.5 Generalization of the problem
5.5.1 Analysis of variance of WIP and CV%
5.6 Set-up activities during style changes
5.7 Conclusion
66
66
68
71
73
74
75
78
v
i_
6. Cellular manufacturing model and work-groups to make 
the flow smooth
6.1 Introduction 82
826.2 Cellular Manufacturing
856.3 Sub-cells (Proposed Cellular manufacturing system) 
6.3.1 86Definition of the proposed sub-cell
Developing the sub-cell concept
Algorithm for balancing the operations in sub-cells
Graphical representation of the sub-cell manufacturing model
Cell Oriented incentive plan
6.3.2 86
6.3.3 96
6.3.4 111
6.3.5 1 12
6.4 Discussion 117
7. Set-up Reduction
7.1 Introduction
7.2 Survey on style changes
7.3 Set-up activity analysis-identifying internal and external set-up 
activities
119
119
122
Visual tool for set-up reduction (Set-up Circle)
7.3.2 Current practice in the set-up process in garment 
manufacturing
7.4 Investigation into the set-up procedure
7.4.1 Analysis of the set-up data
7.5 Minimizing the set-up time
7.5.1 Streamlining the set-up operations through better planning
7.5.2 Set-up circle for garment manufacturing
7.5.3 An alternative approach for set-up operations in garment 
manufacturing
7.3.1 122
123
124
128
129
131
134
135
Discussion7.6 137
8. Implementing sub-cell concept and the set-up procedure
8.1 Introduction
8.2 Current layout of the production line
8.3 Designing sub-cells
8.3.1 Visual controls in sub-cells
8.3.2 Motivation of workgroups
8.3.3 Evaluation of the performance of sub-cells
8.4 Implementing the five step set-up procedure
8.4.1 Evaluation of the five step set-up procedure
8.4.2 First day production efficiency
8.4.3 Cost saving from the set-up improvement
138
138
141
157
158
159
162
164
167
167
vi
1688.5 Discussion
9. Results & Analysis
9.1 Introduction
9.2 Statistical testing on efficiency, quality and absenteeism
9.3 Evaluation of the five-step set-up procedure 
First day production efficiency
Statistical analysis of the reduction in times of set-up elements
9.4 Evaluating the system through questionnaire
9.5 Summary
170
170
172
9.3.1 172
9.3.2 174
177
181
10. Conclusion
10.1 Introduction
10.2 High WIP and its fluctuation
10.3 Sub-cell concept
10.4 Style changes
10.5 Set-up reduction
11.6 Aptness of the research findings across the entire industry
11.7 Research contributions and future directions
183
183
183
185
185
187
187
188List of References
Appendices
Appendix A1 
Appendix A2 
Appendix A3
Questionnaire on waste
Value Stream Map of the current state
Calculated times to move between two sharable 
workstations
Alternative solution for back work group 
System evaluation forms
203
206
208
Appendix A4 
Appendix A5
210
212
Vll
List of Figures
page
222.1 Layouts of straight and cellular systems
272.2 The effect of set-up operations on the line output
2.3 32Impact of six big losses to major competitive factors
3.1 The causes and their significance to late deliveries of the selected 
garment factory for year 2006
53
3.2 Supply chain in manufacturing 53
3.3 The basic processes involved in a garment factory 54
3.4 Sample making process 55
3.5 Processing times of spreading and cutting against the number of 
plies.
The current layout of workstations of a garment manufacturing line
57
5.1 66
5.2 WIP between work stations 68
Capacity times and the takt time5.3 69
WIP fluctuation over the time between workstations5.4 70
Cause and effect diagram of WIP fluctuation5.5 72
Work In Progress between workstations of production line -165.6 74
Work In Progress between workstations of Production Line -185.7 74
Cause and effect diagram for poor line efficiency5.8 78
Comparison of learning effects when operations are shared and 
when not shared (5 cycles)
6.1 95
Comparison of learning effects when operations are shared and 
when not shared (100 cycles of operation change)
Straight line layout
Zigzag layout with the centre table for material handling
U-shaped material flow layout with centre table for material 
handling
U-shaped material flow layout with no centre table 
U-Shaped machine layouts
6.2 95
6.3 100
6.4 100
6.5 101
6.6 101
6.7 101
vm
1076.8 Layout to calculate operator motion times and distances
Flow chart of the algorithm for balancing operations of sub-cells
Cellular manufacturing model to address the problems mentioned 
above
Set-up circle (proposed) for set-up reduction
Significance of each set-up element as a percentage of the total set­
up time
Five-step model for set-up in garment manufacturing
1106.9
6.10 111
1227.1
1287.2
7.3 133
7.4 Set-up circle representing the set-up in the garment industry 134
7.5 Set-up circle for the new set-up approach 135
8.1 The current layout of the production line and the operations carried 139
out
8.2 Layout of the front sub cell 145
8.3 Layout of the back sub-cell 149
8.4 Layout of the Assemble 1 sub cell 152
Layout of the Assemble 2 sub-cell8.5 155
8.6 The layout of the whole production line 156
Visual Controls in controlling production in Cells8.7 157
Display board showing the team identifications8.8 158
WIP between workstations of Line No.2 before and after the 
formation of Cells and the WIP of Line No.3 after implementation 
and the linear trend lines
Monthly efficiencies before November 2006 and the daily 
efficiencies in November of production Line No.2
Customized Microsoft VISIO stencil for layout planning
8.9 160
8.10 162
8.11 163
ix
List of Tables
page
1.1 Improvements achieved by implementing lean 5
2.1 Equipment and product matrix 15
2.2 Product family analysis 16
2.3 Set-up reductions achieved by motor car manufactures 29
3.1 Comparison of labour and machine cost in the garment industry 49
Style changes in the Sri Lankan garment Industry3.2 52
The causes and their significance to late deliveries of a selected 
garment factory for year 2006
Cost of fabrics cutting for different number of plies in a lay
3.3 52
3.4 57
Average WIP, Standard Deviation and CV% of WIP between 
workstations
Average WIP per workstation and the CV% of WIP values of 42 
production lines of 14 different garment manufacturing 
companies
ANOVA table for testing WIP level
5.1 70
5.2
75
5.3 76
ANOVA table for testing WIP fluctuation5.4 77
Operators’ waiting times during style change5.5 79
The efficiency of the production line from the first day of a new 
style until the end of the style
Comparison of different cell types against true cellular 
manufacturing units
5.6 80
6.1
84
Piece numbers and operation times with learning effects when 
operation are shared and not shared
Arbitrarily selected SMVs
6.2 94
6.3 97
SMVs of operations and sum of SMVs6.4 99
Possible operations to be combined under step 1 of the algorithm6.5 100
MTM times for foot, leg, hand and body movements6.6 105
Allowances added and their percentages depending on the work 
environment and complexity of working
6.7
106
x.
:
6.8 Motions and times when moving from B to A 106
6.9 Motions and times when moving from A to B
6.10 Distances and times between workstations for straight line 
layout
107
107
6.11 Distances and times between workstations for zigzag with the 
centre table
6.12 Combined pitch times when three operations are grouped
6.13
108
109
Distances and times required to move within a group for 
different layouts when three operations are combined 110
7.1 Results of the survey on style changes 120
7.2 Changeover times 120
7.3 ANOVA to test whether change over times are high 
Set-up operations during set-up of production Line No. 1
Summarized observations for set-up operations of six production 
lines
122
7.4 124
7.5
125
7.6 Activities during the set-up period and the persons involved 126
Summary of the set-up times and idling times7.7 128
Set-up activities, possibility of converting to external and the 
suggestions to minimize
7.8
129 .
WIP between workstations (of line no.2 producing men’s short)8.1 140
The operations and their SMVs of the front workgroup8.2 142
Operations combined and their combined SMVs for front work 
group
8.3
143
Possible combinations for front sub-cell and the combined SMV 
times
8.4
144
Remaining operations and their times after step 3 of the 
algorithm
The operations and their SMVs of the back, workgroup
Operations combined and their combined SMVs for back work 
group
Operations with SMV less than and more than the pitch time (for 147 
back workgroup)
8.5 145
8.6 146
8.7
147
8.8
xi
8.9 Operations of back cell remaining after the second step of the 
algorithm
8.10 Operations of back cell remaining after the third step of the 
algorithm
8.11 The operations and their SMVs of the assemble I work group
8.12 Operations combined and their combined SMVs of Assemble I 
work group
8.13 Operation combinations selected to share in work group 
Assemblel
8.14 Operations and their SMVs of the assemble 2 work group
8.15 Operations combined and their combined SMVs of Assemble 2 
work group
8.16 Operations with SMV less than and more than the pitch time (for 
Assemble 2 workgroup)
8.17 Operations of back cell remaining after the third step of the 
algorithm
148
149
150
151
152
153
153
154
154
WIP between workstations of Line No.2 and the standard 
deviations before and after the formation of cells
8.18
161
8.19 Times of the set-up activities after implementing the five-step 
set-up procedure
8.20 Summary of the set-up times of each element and its percentage 
improvement after implementing the five step set-up procedure
8.21 First day Efficiencies before and after implementing the five- 
step set-up procedure
9.1 Factory efficiency, defects and operator absenteeism data before 
and after implementing data
9.2 Average and Standard deviation of efficiency, defect and 
absenteeism: before and after implementation
9.3 Average and Standard deviation of the first day efficiency
9.4 Monthly first day production efficiencies and the number of 
style changes before and after implementing the set-up 
procedure and the sub-cells
9.5 Monthly first day production efficiencies
165
166
167
170
171
172
173
173
Xll
:
i_
9.6 Correlation coefficients of the set-up elements
Summary of set-up times before and after implementing the five- 
step set-up procedure
Data on operator and machine idling times for statistical analysis
The ratings given by supervisors and operators on the 
effectiveness of the sub-cell concept
Summarized data on the evaluation of the sub-cell system by the 
operators
Chi-square test and Spearman correlation on operators’ 
evaluation of the system
174
9.7
176
1769.8
9.9
178
9.10
179
9.11
179
Xlll
Abbreviations
ANOVA Analysis of Variance
Acceptable Quality Level
Button Attaching
Button Hole sewing
Board Of Investment
Computer Added Design
Computerized Method Analysis
Computer Method of Sequencing Operations for
Assembly Lines of Assembly Planning and Line
Balancing
Cost Per Minute
Coefficient of Variation
Double Needle Lock Stitch
European Productivity Agency
First In First Out
Feed Off the Arm
Free On Board
Gross Domestic Product
General Sewing Data
Group Technology
International Labour Organization
Joint Apparel Association Forum
Just In Time
Learning Forgetting Curve Model 
Multi Fibre Agreement 
Method Time Measurement 
Make To Order 
No Foreign Exchange 
No Touch Exchange Dies 
Over Lock
Overall Equipment Effectiveness
One Touch Exchange Dies
Product Flow Analysis and Simplification Toolkit
Power Integration Model
Predetermined Motion Time System
Recency Model
Single Minute Exchange Dies
AQL
BA
BH
BOI
CAD
CMA
COMSOAL-PLB
CPM
CV
DNLS
EPA
FIFO
FOA
FOB
GDP
GSD
GT
ILO
JAAF
JIT
LFCM
MFA
MTM
MTO
NFE
NTED
O/L
OEE
OTED
PFAST
PIM
PMTS
RC
SMED
xiv
■SMV
SNLT
Standard Minute Value 
Single Needle Lock Stitch 
Statistical Process Controller 
Time Measurement Unit 
Total Productive Maintenance 
Through Put Time
U.S. International Trading Coorporation
Variance Ratio
Value Stream Mapping
Work In Progress
World Responsible Apparel Production
SPC
TMU
TPM
TPT
USITC
VR
VSM
WIP
WRAP
xv