Analysis of Assembly Line Balancing, in Garment Production by Simulation
Association of Universities for Textiles E-TEAM European Masters in Advanced Textile Engineering "Analysis of Assembly Line Balancing in Garment Production by Simulation” In the context of Lean Manufacturing and the TPS Lina Katharina Rambausek Promoter: Prof Dr Fatma Kalaoğlu, Technical University Istanbul, Istanbul, Turkey Prof Dr Mario Araújo, University of Minho, De Minho, Portugal Academic year: 2007-2008 www.congnhemay.net i Abstract Subject of this dissertation is the analysis of assembly line balancing in garment production by simulation Aspects of Lean Manufacturing (LM) and the Toyota Production System (TPS) will be discussed in reference to the simulation experiments The analysis is accomplished with help of a simulation program, “Enterprise Dynamics” The thesis is developed in connection to the master study program “European Masters in Advanced Textile Engineering” which is organised by the “Association of Universities for Textiles” (AUTEX) The results are based on primary research and knowledge that was gained mainly during the stay at the Technical University Istanbul, Turkey, as well as on field trips to companies in the sector of garment production The dissertation highlights weaknesses and constraints in the application of simulation programs concerning garment production It further explores the opportunities a simulation program could offer European manufacturers in order to stay competitive Also in the textile sector, best practices as they are applied at other producing companies should be considered, and seen as benchmark According to Jeffrey K Liker (2004)1 the Japanese car manufacturer Toyota had it’s origin in the textile sector, the weaving industry It stands to reason that the ideas of the car manufacturing system today could be applied by the way of knowledge transfer to fields of textile production This thesis will focus on the idea of LM (Lean Manufacturing) as well as on the strongly connected TPS (Toyota Production System) The outcomes of this dissertation is intended to give applicants of simulation programs in the textile field an overview about the options to improve their business with simulation It will focus on opportunities and constraints of using a simulation program within the application of production line balancing Keywords: Line Balancing, Garment Manufacturing, Simulation Software, Enterprise Dynamics, Lean Manufacturing, Toyota Production System www.congnhemay.net ii Table of Content ABSTRACT .I TABLE OF CONTENT II LIST OF ILLUSTRATIONS VI LIST OF TABLES VIII LIST OF EQUATIONS X LIST OF ABBREVIATIONS XI PREFACE XII DECLARATION XIII SUMMARY XIV INTRODUCTION .1 OBJECTIVES APPROACH THE MANUFACTURING CONCEPTS 4.1 Progressive Bundle System (PBS) 4.1.1 Concept 4.1.2 Advantages of PBS 4.1.3 Disadvantages of PBS 4.2 Modular Manufacturing (MM) 10 4.2.1 Concept 10 4.2.2 Advantages of MM 11 4.2.3 Disadvantages of MM 12 , 4.3 Lean Manufacturing (LM) 12 4.3.1 Concept 13 4.3.1.1 Pull system 13 4.3.1.2 One-piece flow 14 4.3.1.3 Value-added ratio 14 4.3.1.4 Handling reduction 16 4.3.1.5 Single minute exchange of die (SMED) 16 iii www.congnhemay.net 4.3.1.6 Standard work 16 4.3.1.7 Takt time 16 4.3.1.8 Line balancing 16 4.3.1.9 Productivity 17 4.3.1.10 Flow velocity 17 4.3.2 Advantages of LM: 17 4.3.3 Disadvantages of LM 18 , 4.3.4 Toyota Production System 18 4.4 Mixed Manufacturing Module Design - Hybrid Version 21 ISTCOMP .22 5.1 Data base 22 5.2 Product 22 5.3 Layout 23 5.3.1 Section I & II in detail 29 5.3.2 I Body - Subassembly 30 5.3.3 II Collar and Lining Subassembly 34 5.3.4 Section III.& IV in detail 38 5.3.5 III Sleeve Subassembly 39 5.3.6 IV Final Assembly 41 5.3.7 Workforce 45 5.4 The work flow 49 5.5 Time Studies 55 LINE BALANCING 59 , 6.1 Line Balancing in general 59 6.2 Line balancing at HUGO BOSS 66 6.2.1 Introduction 66 6.2.2 Production site 66 6.2.3 Workforce 67 6.2.4 General system of planning: 67 6.2.5 Efficiency 69 6.2.6 Special conditions in Dynamic lines 73 6.3 Simulation 74 6.4 Line Balancing in garment production 75 SOFTWARE ENTERPRISE DYNAMICS, 77 ,,, 7.1 Application 77 7.1.1 Model 77 7.1.2 Simulate 78 7.1.3 Visualize 78 7.1.4 Control 78 7.2 User 79 7.3 Data 82 8.1 8.2 8.3 SIMULATION MODEL 83 Simplifications 83 Aspects of Lean Manufacturing 84 Setup process 85 EXPERIMENTS .93 9.1 Experiment A0 97 9.1.1 Results of experiment A0 97 9.2 Experiment A1 99 9.2.1 Improvement strategy - Experiment A1 99 www.congnhemay.net iv 9.2.2 A1 Changes 101 9.2.3 Results of experiment A1 103 9.3 Experiment A2 103 9.3.1 Improvement strategy - Experiment A2 103 9.3.2 A2 Changes 103 9.3.3 Results of Experiment A2: 106 9.4 Experiment A3 106 9.4.1 Improvement strategy - Experiment A3 106 9.4.2 A3 Changes 106 9.4.3 Results of experiment A3 107 9.5 Experiment A4 107 9.5.1 Improvement strategy - Experiment A4 108 9.5.2 A4 Changes 108 9.5.3 Results of experiment A4 108 9.6 Overview experiment A 109 9.6.1 Output 110 9.6.2 Takt time 111 9.6.3 Number of operators 112 9.6.4 Productivity per operator 113 9.6.5 Average content in subassembly queues 114 9.6.6 Average stay time of the product in the queue 116 9.6.7 WIP values 119 9.6.8 Throughput time 120 9.7 Experiment B 121 9.8 Experiment B1 121 9.8.1 Improvement strategy - Experiment B1 121 9.8.2 B1 Changes 121 9.8.3 Results of experiment B1 124 9.9 Experiment B2 124 9.9.1 Improvement strategy - Experiment B2 125 9.9.2 B2 Changes 125 9.9.3 Results of experiment B2 126 9.10 Overview experiment B 127 9.10.1 Output 127 9.10.2 Number of Operators 128 9.10.3 Productivity per operator 130 10 CONCLUSION 133 10.1 10.2 10.3 10.4 10.5 10.6 Strengths 133 Weaknesses 134 Opportunities 135 Threats 135 Personal problems of the author 136 Future outlook 137 A APPENDIX A 139 A.1 List of minimum wages by country 139 B APPENDIX B 141 B.1 Data Basis – Machinery 141 C APPENDIX C 147 C1 ED System requirements: 147 D APPENDIX D 148 www.congnhemay.net D1 E v Simulation Model Layout 148 APPENDIX E .149 Overview experiment A 149 E1 Output of the sections individually 149 E2 Number of operators per section 150 E3 Number of operators per section 152 F APPENDIX F .154 Overview experiment B 154 F1 List of operators and their assignments to servers according to Layout of ISTCOMP 154 BIBLIOGRAPHICAL REFERENCES 156 www.congnhemay.net List of Illustrations Fig 3-1 Procedural method Fig 4-1 Value added vs Non-value-added activities 15 Fig 4-2 Potential effect on Lead time after reducing non-value-added activities by 50% 15 Fig 4-3 Decision tree for evaluation of processes 20 Fig 5-1 Ladies’ jacket basic model 23 Fig 5-2 Drawing of ladies’ jacket production line (sections I & II) 24 Fig 5-3 Advanced sketch of the production line (all sections) 24 Fig 5-4 Layout ladies’ jacket production line, work flow at 22.02.2008 27 Fig 5-5 Layout ladies’ jacket production line, work flow at 22.02.2008 (part1/2) 29 Fig 5-6 Area which is worked-on in section I Body 30 Fig 5-7 Parts which are worked on in section II.C&L 34 Fig 5-8 Layout Ladies’ jacket production line, work flow at 22.02.2008 (part2/2) 38 Fig 5-9 Parts which are sub-assembled in section III 39 Fig 5-10 Parts which are assembled in section IV: 41 Fig 5-11 Number of workers I 46 Fig 5-12 Number of workers II 46 Fig 5-13 Average age of the workers 47 Fig 5-14 Average experience in this job 47 Fig 5-15 Number of operations the operators are trained-in 48 Fig 5-16 Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 50 Fig 5-17 Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part1/4) 51 Fig 5-18 Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part2/4) 52 Fig 5-19 Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part3/4) 53 Fig 5-20 Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part4/4) 54 Fig 5-21 REFA standard form for time studies 56 Fig 5-22 REFA standard form for time studies additional side 57 Fig 6-1 Work element sharing 63 Fig 6-2 Division of work element 64 Fig 6-3 Assembly sequence 65 Fig 6-4 Hierarchies at HB 67 Fig 7-1 Logo of the simulation software Enterprise Dynamics 77 Fig 7-2 VR-simulation of a warehouse system & a production line with the ED Logistic Suite 80 Fig 8-1 The layout of the simulation model 85 Fig 8-2 The atoms source, queue, server and assembler 86 Fig 8-3 Simulation model after the channels are connected 86 Fig 8-4 Simulation model after the channels are connected (more detailed) 87 Fig 8-5 Application of the values of operation in “Stat:Fit” 88 Fig 8-6 Changing the atoms properties 90 Fig 8-7 After a test run of 90 hours the output volume is 7582 units 91 Fig 8-8 3D Model View after inserting the atom “VR building” 92 Fig 9-1 Experimentation Wizard 95 Fig 9-2 Experimentation Wizard, Performance Measures PFM 96 Fig 9-3 Library Tree ED 100 Fig 9-4 Status Monitor 100 Fig 9-5 Monitor 101 Fig 9-6 Output per shift of entire production line 110 Fig 9-7 Takt time of the entire production line 111 Fig 9-8 Total number of operators of the production line 112 Fig 9-9 Productivity per operator [units/operator] 113 Fig 9-10 Average content in the section’s queues 115 Fig 9-11 Average content in the section queue IIIb Sleeve Prep 116 Fig 9-12 Average stay time in the section’s queues 118 Fig 9-13 Average stay time in the section IIIb Sleeve Preparation Queue 118 Fig 9-14 WIP values of the entire production line according to values of A0 to A4 119 Fig 9-15 Throughput time of the entire production line according to values of A0 to A4 120 vi www.congnhemay.net Fig 9-16 Total output of the entire production line 127 Fig 9-17 Number of operators entire production line 128 Fig 9-18 Number of operators per section 130 Fig 9-19 Prodctivity per worker 131 Fig 9-20 Overview B - Productivity of operators per section 132 Fig B-1 Machinery at ISTCOMP within the sections I Body and II C&L 145 Fig B-2 Machinery at ISTCOMP within the sections III Sleeve and IV Assembly 146 Fig D-1 “Enterprise Dynamics” simulation model layout 148 Fig D-2“Enterprise Dynamics” simulation model layout with connections 148 vii www.congnhemay.net List of Tables Table 4-1 Areas in which waste can be avoided 19 Table 5-1 Example: Code in section II Collar & Lining 25 Table 5-2 Example: Code in section II Collar & Lining 26 Table 5-3 Number of operations per section 28 Table 5-4 Operations of section I Body - Subassembly (part 1/4) 30 Table 5-5 Operations of section I Body - Subassembly (part 2/4) 31 Table 5-6 Operations of section I Body - Subassembly (part 3/4) 32 Table 5-7 Operations of section I Body - Subassembly (part 4/4) 33 Table 5-8 Operations of section II Collar and Lining - Subassembly (part 1/4) 34 Table 5-9 Operations of section II Collar and Lining - Subassembly (part 2/4) 35 Table 5-10 Operations of section II Collar and Lining - Subassembly (part 3/4) 36 Table 5-11 Operations of section II Collar and Lining - Subassembly (part 4/4) 37 Table 5-12 Operations section III Sleeve Subassembly (part 1/2 39 Table 5-13 Operations section III Sleeve Subassembly (part 2/2) 40 Table 5-14 Operations of section IV Final Assembly (part 1/4) 41 Table 5-15 Operations of section IV Final Assembly (part 2/4) 42 Table 5-16 Operations of section IV Final Assembly (part 3/4) 43 Table 5-17 Operations of section IV Final Assembly (part 4/4) 44 Table 5-18 Number of workers per section 45 Table 5-19 Standard symbols determined by The American Society of Mechanical Engineers 49 Table 6-1 Example calculation 60 Table 6-2 Example calculation 62 Table 6-3 Example calculation 62 Table 6-4 Example: Operator A fulfils different operations 71 Table 6-5 Line balancing sheet at HB 72 Table 7-1 Overview Application fields and clients 79 Table 8-1 Operations and their distributions (part 1/3) 88 Table 8-2 Operations and their distributions (part 2/3) 89 Table 8-3 Operations and their distributions (part 3/3) 90 Table 9-1 Output values experiment A0 98 Table 9-2 Input values experiment A0 98 Table 9-3 A1 - 1st Change - results gained through simulation 101 Table 9-4 A1 2nd Change - results gained through simulation 102 Table 9-5 Effect of the changes in experiment A1 102 st Table 9-6 A2 Change - results gained through simulation 104 nd Table 9-7 A2 Change - results gained through simulation 104 rd Table 9-8 A2 Change - results gained through simulation 105 th Table 9-9 A2 Change - results gained through simulation 105 Table 9-10 Effect of the changes in experiment A2 105 Table 9-11 A3 Changes- results gained through simulation 107 Table 9-12 A4 changes – Reduction in queue size 108 Table 9-13 A4 Change in WIP value 109 Table 9-14 A4 Change in Throughput time 109 Table 9-15 Overview experiment A – Output volume of the entire manufacturing line (1/2) 110 Table 9-16 Overview experiment A – Output volume of the entire manufacturing line (2/2) 110 Table 9-17 Overview experiment A – Takt time of the entire production line 111 Table 9-18 Overview experiment A – Number of operators of the entire production line 112 Table 9-19 Overview experiment A – Productivity of operators (output/no of operator) 113 Table 9-20 Overview experiment A – Average content in queue of section I Body 114 Table 9-21 Overview experiment A – Average content in queue of section II Collar & Lining 114 Table 9-22 Overview experiment A – Average content in queue of section III Sleeve 114 Table 9-23 Overview experiment A – Average content in queue of section IIIb Sleeve Prep 115 Table 9-24 Overview experiment A – Average stay time in queue of section I Body 116 Table 9-25 Overview experiment A – Average stay time in queue of section II Collar & Lining116 Table 9-26 Overview experiment A – Average stay time in queue of section III Sleeve 117 viii www.congnhemay.net Table 9-27 Overview experiment A – Average stay time in queue of section IIIb Sleeve Prep.117 Table 9-28 Overview experiment A – WIP values 119 Table 9-29 Overview experiment A – Throughput time of the production line 120 Table 9-30 Number of operators entire line 124 Table 9-31 Output entire line 124 Table 9-32 Number of operators of the entire production line 126 Table 9-33 Output volume of the total production line 126 Table 9-34 Overview B - Output of the entire production line 127 Table 9-35 overview B – Total number of Operators 128 Table 9-36 overview B – Total number of Operators comparison A0 to B2 128 Table 9-37 Overview B - Operator number within section I Body 129 Table 9-38 Overview B - Operator number within section IV Assembly 129 Table 9-39 Overview B – Productivity per operator entire production line 130 Table 9-40 Overview B – Productivity per operator entire production line, A0 vs B2 130 Table 9-41 Overview B - Productivity of operators in section I Body 131 Table 9-42 Overview B - Productivity of operators in section II C&L 131 Table 9-43 Overview B - Productivity of operators in section III Sleeve 132 Table 9-44 Overview B - Productivity of operators in section IV Assembly 132 Table A-1 Monthly gross minimum wage rates of an full-time adult employees aged 23+ [1] 139 Table B-1 Machinery at ISTCOMP 141 Table C-1 Hardware configurations 147 Table E-1 Overview experiment A – Output volume per shift section I Body 149 Table E-2 Overview experiment A – Output volume per shift section II Collar & Lining 149 Table E-3 Overview experiment A – Output volume Section III Sleeve 149 Table E-4 Overview experiment A – Output volume section IIIb Sleeve Preparation 150 Table E-5 Overview experiment A – Number of operators in section I Body and II C&L 150 Table E-6 Overview experiment A – Number of operators in section II C&L 150 Table E-7 Overview experiment A – Number of operators in section III Sleeve 151 Table E-8 Overview experiment A – Number of operators in section IIIb Sleeve Prep 151 Table E-9 Overview experiment A – number of operators in section IV Assembly 151 Table E-10 Overview experiment A – Productivity of operators per output value in section I 152 Table E-11 Overview experiment A – Productivity of operators per output value in section II 152 Table E-12 Overview experiment A – Productivity of operators per output value in section III.152 Table E-13 Overview experiment A – Productivity of operators per output value in section IIIb.153 Table E-14 Overview experiment A – Productivity of operators per output value in section IV.153 Table F-1 Assignment of operators to operations at ISTCOMP (part 1/2) 154 Table F-2 Assignment of operators to operations at ISTCOMP (part 22) 155 ix Appendix D 148 D Appendix D D1 Simulation Model Layout Fig D-1 and Fig D-2 show the layout of the simulation model generated with the Logistics Suite of Enterprise Dynamics Fig D-1 “Enterprise Dynamics” simulation model layout 136 Fig D-2“Enterprise Dynamics” simulation model layout with connections 137 Appendix E 149 E Appendix E Overview experiment A E1 Output of the sections individually The output of the section is shown of each section individually, and then the change in output volume Table E-1 to Table E-9 Table E-1 Overview experiment A – Output volume per shift section I Body I Body Input queue Change in value Change in % A 712,16 A1 925,81 213,65 30,00 A2 925,62 -0,19 -0,02 A3 921,82 -3,80 -0,41 A4 921,92 0,10 0,01 Table E-2 Overview experiment A – Output volume per shift section II Collar & Lining II C&L Input queue Change in value Change in % A 809,96 A1 810,02 0,06 0,01 A2 981,81 171,79 21,21 A3 981,02 -0,79 -0,08 A4 921,92 -59,10 -6,02 Table E-3 Overview experiment A – Output volume Section III Sleeve III Sleeve Input queue Change in value Change in % A 1436,08 A1 1587,12 151,04 10,52 A2 1844,54 257,42 16,22 A3 1844,38 -0,16 -0,01 A4 1842,05 -2,33 -0,13 150 Appendix E Table E-4 Overview experiment A – Output volume section IIIb Sleeve Preparation IIIb Sleeve Prep Input queue Change in value Change in % A 712,12 A1 762,43 50,31 7,06 A2 925,34 162,91 21,37 A3 921,94 -3,40 -0,37 A4 921,84 -0,10 -0,01 E2 Number of operators per section Table E-5 Overview experiment A – Number of operators in section I Body and II C&L I Body No of operators change in value change in % A0 31 - - A1 32 0,03 A2 32 0,00 A3 27 -5 -0,16 A4 27 0,00 Table E-6 Overview experiment A – Number of operators in section II C&L II C&L No of operators change in value change in % A0 30 - - A1 30 0,00 A2 30 0,00 A3 26 -4 -0,13 A4 26 0,00 0,00 151 Appendix E Table E-7 Overview experiment A – Number of operators in section III Sleeve III Sleeve No of operators change in value change in % A0 19 - - A1 20 0,05 A2 20 0,00 A3 19 -1 -0,05 A4 19 0,00 Table E-8 Overview experiment A – Number of operators in section IIIb Sleeve Prep IIIb Sleeve Prep No of operators change in value change in % A0 - - A1 0,00 A2 0,00 A3 0,00 A4 0,00 Table E-9 Overview experiment A – number of operators in section IV Assembly No of operators change in value change in% A0 42 - - A1 42 0,00 A2 42 0,00 A3 36 -6 -0,14 A4 36 0,00 152 Appendix E E3 Number of operators per section Table E-10 Overview experiment A – Productivity of operators per output value in section I Productivity per worker no Of workers input queue Output/worker change in value change in % A0 31 712,16 22,97 - - A1 32 925,81 28,93 5,96 0,26 A2 32 925,62 28,93 -0,01 0,00 A3 27 921,82 34,14 5,22 0,18 A4 27 921,92 34,15 0,00 0,00 Table E-11 Overview experiment A – Productivity of operators per output value in section II Productivity per worker No Of workers Input queue Output/worker Change in value Change in % A0 30 809,96 27,00 - - A1 30 810,02 27,00 0,00 0,00 A2 30 981,81 32,73 5,73 0,21 A3 26 981,02 37,73 5,00 0,15 A4 26 921,92 35,46 -2,27 -0,06 Table E-12 Overview experiment A – Productivity of operators per output value in section III Productivity / worker No Of workers Input queue Output/worker Change in value Change in % A0 19 1436,08 75,58 - - A1 20 1587,12 79,36 3,77 0,05 A2 20 1844,54 92,23 12,87 0,16 A3 19 1844,38 97,07 4,85 0,05 A4 19 1842,05 96,95 -0,12 0,00 153 Appendix E Table E-13 Overview experiment A – Productivity of operators per output value in section IIIb Productivi ty / worker No of workers Input queue Output/wo rker change in value change in % A0 712,12 712,12 - - A1 762,43 762,43 50,31 0,07 A2 925,34 925,34 162,91 0,21 A3 921,94 921,94 -3,40 0,00 A4 921,84 921,84 -0,10 0,00 Table E-14 Overview experiment A – Productivity of operators per output value in section IV Productivity / worker No of workers Input queue Output/worker Change in value Change in % A0 42 712,15 16,96 - - A1 42 762,37 18,15 1,20 0,07 A2 42 925,34 22,03 3,88 0,21 A3 36 921,91 25,61 3,58 0,16 A4 36 921,85 25,61 0,00 0,00 Appendix F 154 F Appendix F Overview experiment B F1 List of operators and their assignments to servers according to Layout of ISTCOMP Table F-1 Assignment of operators to operations at ISTCOMP (part 1/2) I-25 18 III-3-49 45, 49, 51 Operation Operator Number of Operation Operator Number of Operation Operator Operator I-1 Number of Operation Number of IV-13-73 66 III-4-50 46, 53 IV-14-74 67, 68, 69 I-2 I-26 19, 20 I-3 I-27 20, 21 III-5-51 47 IV-15-75 71 I-4 II-1-28 22, 27 III-6-52 48 IV-16-76 71 III-7-53 49 IV-17-77 71 I-5 II-2-29 23, 24, 25, 31 I-6 II-3-30 30, 31 III-8-54 50, 52 IV-18-78 72, 73 I-7 II-4-31 26 III-9-55 54 IV-19-79 74 I-8 II-5-32 28, 29 III-10-56 55 IV-20-80 75 I-9 II-6-33 32 III-11-57 56, 51 IV-21-81 75 I-10 II-7-34 33 III-12-58 56 IV-22-82 76 I-11 12 II-8-35 35 III-13-59 55 IV-23-83 77 I-12 13 II-9-36 36 III-14-60 57 IV-24-84 78 155 Appendix F Table F-2 Assignment of operators to operations at ISTCOMP (part 22) Operation Operator Number of Operation Operator Number of Operation Operator Operator Number of Operation Number of I-13 14 II-10-37 34 IV-1-61 58 IV-25-85 78 I-14 7, 15 II-11-38 37 IV-2-62 59 IV-26-86 78 I-15 16 II-12-39 38 IV-3-63 59 IV-27-87 79 I-16 16 II-13-40 39 IV-4-64 60 IV-28-88 80, 81 I-17 16 II-14-41 40 IV-5-65 61, 63 IV-29-89 82 I-18 16 II-15-42 40 IV-6-66 62 IV-30-90 83 I-19 17 II-16-43 41 IV-7-67 62 IV-31-91 84 I-20 II-17-44 41 IV-8-68 62 IV-32-92 83 I-21 II-18-45 42 IV-9-69 62 IV-33-93 85 I-22 10 II-19-46 42, 43 IV-10-70 64, 65 IV-34-94 85 I-23 11 III-1-47 44 IV-11-71 66 IV-35-95 85 I-24 18 III-2-48 44 IV-12-72 66 IV-36-96 85 Bibliographical references 156 Bibliographical references [1] J K LIKER (c2004): The Toyota way: 14 management principles from the world’s greatest manufacturer, New York, McGrawhill [2] G.FOZZARD / J.SPRAGG / D.TYLER (1995): Simulation of flow lines in clothing manufacture, International Journal of Clothing , Science and Technology, MCB University Press., Vol.8 No.4, pp.17-27 [3] O KUTZ / C ZERRES / M ZERRES, „Wertkettenanalyse“, date of publication: unknown, URL: http://www.studentensupport.de (10.03.2008, 16:41) [4] A C CAPUTO / M PALUMBO (2005): Manufacturing re-insourcing in the textile industry, Emerald group publishing Ltd., Industrial Management & Data Systems, Vol 105, No.2 [5] S KURSUN / M DINCMEN / F KALAOGLU (2007): Production Line Modelling in Textile Industry by Simulation and Determination of suitable job flow, Technical University Istanbul [6] G.FOZZARD / J.SPRAGG / D.TYLER (1995): Simulation of flow lines in clothing manufacture, International Journal of Clothing , Science and Technology, MCB University Press., Vol.8 No.4, pp.17-27 [7] A C CAPUTO / M PALUMBO (2005): Manufacturing Re-insourcing in the Textile Industry, Emerald group publishing Ltd., Industrial Management & Data Systems, Vol 105, No.2 [8] SOCIETY OF MANUFACTURING ENGINEERS (2004): China is loosing more manufacturing jobs in U.S., New York 2004, URL: http://www.sme.org/cgi-bin/getpress.pl?&&20041170&ND&&SME& (26.03.2008, 5:00) [9] R MOSSER BARNES (1980): Equation “Productivity” [10] R MOSSER BARNES (1980): “Motion and Time Study - Design and Measurement of work”, 7th edition, John Wiley & Sons Editorial, New York [11] R MOSSER BARNES (1980): Equation “Labour productivity” [12] R MOSSER BARNES (1980): Equation “Takt Time” [13] G.FOZZARD / J.SPRAGG / D.TYLER (1995): Simulation of flow lines in clothing manufacture, International Journal of Clothing , Science and Technology, MCB University Press., Vol.8 No.4, pp.17-27 [14] L RAMBAUSEK (2008): Figure “Procedural method” [15] P.A FERRINGTON / B.J SCHROER / J.J SWAIN, Y FENG (1994): “Simulators as a tool for rapid manufacturing simulation”, Proceedings of the 1994 winter Simulation Conference [16] J WANG / B.J SCHROER / M.C ZIEMKE (1991): “Understanding modular manufacturing in the apparel industry using simulation”, Proceedings of the 1991 Winter Simulation Conference [17] F KALAOĞLU / C SARICAN (2007): “Analysis of modular Manufacturing System in Clothing Industry by USING Simulation“, Fibres and Textiles in eastern Europe, Vol 15, No.3 (62) [18] 1996 - 2006 PROCESS QUALITY ASSOCIATES INC (2008): Lean manufacturing, http://www.pqa.net/ProdServices/leanmfg/lean.html (14.6.2008, 15:32) Bibliographical references 157 [19] JAMES P WOMACK / DANIEL T JONES (C1996): Lean Thinking: Banish Waste and Create Wealth in your Corporation [electronic resource], Simon & Schuster, New York [20] M.A YOUSSEF (1994): Agile manufacturing: the battleground for competition in the 1990s and beyond”, International Journal of Operations & Production Management, Vol 14, No.11, pp.46 [21] G CONNER (2001): Lean Manufacturing for the Small Shop, Society of Manufacturing Engineers, Dearborn, Michigan [22] G CONNER (2001): Equation “Lead time” [23] G CONNER (2001): Equation “Value added ratio” [24] G CONNER (2001): Lean Manufacturing for the Small Shop, Society of Manufacturing Engineers, Dearborn, Michigan [25] G CONNER (2001): Lean Manufacturing for the Small Shop, Society of Manufacturing Engineers, Dearborn, Michigan [26] R MOSSER BARNES (1980): Equation “Takt time” [27] G CONNER (2001): Lean Manufacturing for the Small Shop, Society of Manufacturing Engineers, Dearborn, Michigan [28] JAMES P WOMACK / DANIEL T JONES (c1996): Lean Thinking: Banish Waste and Create Wealth in your Corporation [electronic resource], Simon & Schuster, New York [29] L RAMBAUSEK (2008): Table “Areas in which waste can be avoided” [30] L RAMBAUSEK (2008): Figure “Decision Tree for the Evaluation of Processes” [31] A C CAPUTO / M PALUMBO (2005): Manufacturing Re-insourcing in the textile industry, Emerald group publishing Ltd., Industrial Management & Data Systems, Vol 105, No.2 [32] T PARDI (2007): Redefining the Toyota Production System: The European side of the story, New Technology, Work and Employment, journal compilation, Blackwell publishing Ltd., Oxford [33] G CONNER (2001): Lean Manufacturing for the Small Shop, Society of Manufacturing Engineers, Dearborn, Michigan [34] ISTCOMP (2008): Figure “Ladies’ jacket basic model” [35] L RAMBAUSEK (2008): Figure “Drawing of ladies’ jacket production line (sections I & II)” [36] L RAMBAUSEK (2008): Figure “Advanced sketch of the production line (all sections)” [37] L RAMBAUSEK (2008): Figure “Layout ladies’ jacket production line, work flow at 22.02.2008” [38] L RAMBAUSEK (2008): Figure “Layout ladies’ jacket production line, work flow at 22.02.2008 (part1/2)” [39] L RAMBAUSEK (2008): Figure “Area which is worked-on in section I Body” [40] L RAMBAUSEK (2008): Figure “Parts which are worked on in section II.C&L” [41] L RAMBAUSEK (2008): Figure “Layout Ladies’ jacket production line, work flow at 22.02.2008 (part2/2)” Bibliographical references 158 [42] L RAMBAUSEK (2008): Figure “Parts which are sub-assembled in section III” [43] L RAMBAUSEK (2008): Figure “Parts which are assembled in section IV” [44] L RAMBAUSEK (2008): Figure “Number of workers I” [45] L RAMBAUSEK (2008): Figure “Number of workers II” [46] L RAMBAUSEK (2008): Figure “Average age of the workers” [47] L RAMBAUSEK (2008): Figure “Average experience in this job” [48] L RAMBAUSEK (2008): Figure “Number of operations the operators are trained-in” [49] R MOSSER BARNES, “Motion and Time Study - Design and Measurement of work”, 7th edition, John Wiley & Sons Editorial, New York, 1980 [50] standard symbols determined by “The American Society of Mechanical Engineers” [51] L RAMBAUSEK (2008): Figure “Work flow chart Ladies’ jacket production line, work flow at 22.02.2008” [52] L RAMBAUSEK (2008): Figure “Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part1/4)” [53] L RAMBAUSEK (2008): Figure “Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part2/4)” [54] L RAMBAUSEK (2008): Figure “Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part3/4)” [55] L RAMBAUSEK (2008): Figure “Work flow chart Ladies’ jacket production line, work flow at 22.02.2008 (part4/4)” [56] R MOSSER BARNES (1980): Motion and Time Study - Design and Measurement of work, 7th edition, John Wiley & Sons Editorial, New York [57]REFA – Verband für Arbeitsstudien und Betriebsorganisation E.V., Darmstadt “REFAZeitaufnahmebogen Z2 für Abläufe mit Wiederholungen” , Beuth Verlag GmbH, Berlin und Köln [58]REFA – Verband für Arbeitsstudien und Betriebsorganisation E.V., Darmstadt “Ergänzungsbogen zu REFA-Zeitaufnahmebogen Z2” , Beuth Verlag GmbH, Berlin und Köln [59]REFA – Verband für Arbeitsstudien und Betriebsorganisation E.V., Darmstadt: Equation “Average of measured times” [60]REFA – Verband für Arbeitsstudien und Betriebsorganisation E.V., Darmstadt: Equation “Standard time” [61] S KURSUN / M DINCMEN / F KALAOGLU (2007): Production Line Modelling in Textile Industry by Simulation and Determination of suitable job flow, Technical University Istanbul [62] A.J CHUTER (1998): Introduction to clothing production management, Wrenbury Associates, Leeds [63] B NIEBEL / A FREIVALS (2003): International Edition Methods, Standards, and work design”, 11th edition, McGraw-Hill 159 Bibliographical references [64] B NIEBEL / A FREIVALS (2003): International Edition Methods, Standards, and work design”, 11th edition, McGraw-Hill [65] B NIEBEL / A FREIVALS (2003): International Edition Methods, Standards, and work design”, 11th edition, McGraw-Hill [66] B NIEBEL / A FREIVALS (2003): International Edition Methods, Standards, and work design”, 11th edition, McGraw-Hill [67] L RAMBAUSEK (2008): Figure “Work element sharing” [68] L RAMBAUSEK (2008): Figure “Division of work element” [69] L RAMBAUSEK (2008): Figure “Assembly sequence” [70] L RAMBAUSEK (2008): Figure “Hierarchies at HB” [71] HUGO BOSS, Izmir (2008): Equation “Group efficiency” [72] HUGO BOSS, Izmir (2008): Equation “Group performance” [73] HUGO BOSS, Izmir (2008): Equation “Personal efficiency” [74] HUGO BOSS, Izmir (2008): Equation “Personal performance” [75] HUGO BOSS, Izmir (2008): Equation “Output volume according to HB 76 Z.X GUO, W.K WONG, S.Y.S LEUNG, J.T FAN, J.T., S.F CHAN (2007): Genetic optimization of order scheduling with multiple uncertainties, with Applications, published online doi:10.1016/j.eswa.2007.08.058 Expert Systems 77 W.K WONG, S.Y.S LEUNG, P.Y MOK (2006): Developing a genetic optimisation approach to balancing an apparel assembly line, International Journal of Advanced Manufacturing Technology, Vol.28, pp.387-394 78 B.L SONG / W.K WONG / J.T FAN / S.F CHAN (2006): A recursive operator allocation approach for assembly line-balancing optimization problem with the consideration of operator efficiency, Computers & Industrial Engineering, 51, p 585-608 79 W.K WONG, S.Y.S LEUNG, P.Y MOK (2006): Developing a genetic optimisation approach to balancing an apparel assembly line, Manufacturing Technology, Vol.28, pp.387-394 International Journal of Advanced 80 K.C.C CHAN / P.C.L HUI / K.W: YEUNG / F.S.F NG (1998): Handling the assembly line balancing problem in clothing industry using a generic algorithm, International Journal of Clothing Science and Technology, Vol 10 No 1, p.21-37 81 C BECKER / A SCHOLL (2006): A SURVEY ON PROBLEMS AND METHODS IN GENERALIZED Assembly Line Balancing, European Journal of Operational Research 168(3) 694-715 [82] P.C.L HUI / K.C.K CHAN / K.W YEUNG (1996): Modelling job complexity in garment manufacture by inductive learning, International Journal of Clothing Science and Technology, Vol No 1, p.34-44 160 Bibliographical references [83] Z.X GUO, W.K WONG, S.Y.S LEUNG, J.T FAN, J.T., S.F CHAN (2007): Genetic optimization of order scheduling with multiple uncertainties, with Applications, published online doi:10.1016/j.eswa.2007.08.058 Expert Systems [84] Z.X GUO, W.K WONG, S.Y.S LEUNG, J.T FAN, J.T., S.F CHAN (2007),: Genetic optimization of order scheduling with multiple uncertainties, with Applications published online doi:10.1016/j.eswa.2007.08.058 Expert Systems [85] P.C.L HUI / K.C.K CHAN / K.W YEUNG (1996): Modelling job complexity in garment manufacture by inductive learning, International Journal of Clothing Science and Technology, Vol No 1, p.34-44 [86] R.MANZINI / E FERRARI / M GAMBERI (2005): Simulation performance in the optimisation of the supply chain, Journal of Manufacturing Technology, Vol 16, No 2, p.127-144 [87] C ANDRÉS / C MIRALLES / R PASTOR (2008): Balancing and scheduling tasks in assembly lines with sequence-dependent setup times, European Journal of Operational Research, 187, p.1212-1223 [88] N BOYSEN / M FLIEDNER / A SCHOLL (2008): Assembly line balancing: Which model to use when?, International Journal of production Economics, 111, 509-528 [89] A SCHOLL / C BECKER (2006): State-of-the-art Exact and Heuristic Solution Procedures for Simple Assembly Line Balancing, European Journal of Operational Research 168(3) p 666-693 [90] R GAMBERINI / A GRASSI / B RIMINI (2006): A New Multi-objective Heuristic Algorithm for Solving the Stochastic Assembly Line International Journal of Production Economics 102(2) 226-243 Re-balancing Problem, 91 W.K WONG /C.K KWONG / P.Y MOK, / W.H IP (2006): Genetic Optimization of JIT Operation Schedules for Fabric-cutting Process in Apparel Manufacture, Journal of Intelligent Manufacturing 17(3), 341-354 92 Z.X GUO / W.K WONG / S.Y S LEUNG / J.T FAN / S.F CHAN (2006): Mathematical Model and Genetic optimization for the job shop scheduling problem in a mixed- and multi-product assembly environment: A case study based on apparel industry, Computers & Industrial Engineering, 50, p 202-219 93 S G DIMITRIADIS (2006): Assembly line balancing and group working: a heuristic procedure for workers’ groups operating on the same product and workstation, Computers & Operations Research, 33, p 2757-2774 94 Y.K.KIM / W.S SONG / J H KIM (2007): A mathematical model and a generic algorithm for two-sided assembly line balancing, Computers & Operations Research 95 J F O’KANE (2003): Simulation as enabler for organisational excellence, Measuring Business Excellence, Vol 7, No 4, p 12-19 96 K.C.C CHAN / P.C.L HUI / K.W: YEUNG / F.S.F NG (1998): Handling the assembly line balancing problem in clothing industry using a generic algorithm, International Journal of Clothing Science and Technology, Vol 10 No 1, p.21-37 Bibliographical references 161 97 N.BOYSEN / M FLIEDNER / A SCHOLL (2007): A classification of assembly line balancing problems, European Journal of Operational Research, 183, p 674-693 [98] Incontrol Enterprise Dynamics (2008), URL: http://www.incontrol.nl/?to=products (28.04.2008, 17:43) [99] Enterprise Dynamics®7, Tutorial ED7, Educational Single-User Licence, Incontrol simulation software B.V., The Netherlands Training Basics [100] Incontrol Enterprise Dynamics (2008): Figure “Logo of the simulation software Enterprise Dynamics” [101] A E RIZZOLI (2007): A Collection of Modelling and Simulation Resources on the Internet, URL: http://www.idsia.ch/~andrea/simtools.html (28.04.2008, 18:17) [102] SIMARON (2008): URL: http://www.simaron.com/ED.htm?to=references_harbor (26.07.2008 11:58) [103] W B NORDGREN (2001): Taylor enterprise dynamics, Winter Simulation Conference, Proceedings of the 33rd conference on Winter simulation, Arlington, Virginia, p.69 – 271 [104] L GOULD (unknown): Simulation: The Real Story, Gardner Publications Inc., URL: http://www.autofieldguide.com/articles/010202.html (14.6.2008, 15:45) [105] Incontrol Enterprise Dynamics (2008), URL: http://www.incontrol.nl (28.04.2008, 17:33) [106] Incontrol Enterprise Dynamics (2008): Figure “VR-simulation of a warehouse system and a production line with the ED Logistic Suite” [107] Incontrol Enterprise Dynamics (2008), URL: http://www.incontrol.nl/?to=features (28.04.2008, 17:50) [108] Incontrol Enterprise Dynamics (2008), URL: http://www.enterprisedynamics.com/?to=downloads (28.04.2008, 18:02) [109] G.FOZZARD / J.SPRAGG / D.TYLER, 1995, Simulation of flow lines in clothing manufacture, International Journal of Clothing , Science and Technology, Vol.8 No.4, pp.17-27, MCB University Press [110] L GOULD (unknown): Simulation: The Real Story, Gardner Publications Inc., URL: http://www.autofieldguide.com/articles/010202.html (14.6.2008, 15:45) [111] L RAMBAUSEK (2008): Figure “The layout of the simulation model” [112] L RAMBAUSEK (2008): Figure “The atoms source, queue, server and assembler” [113] L RAMBAUSEK (2008): Figure “Simulation model after the channels are connected” [114] L RAMBAUSEK (2008): Figure “Simulation model after the channels are connected (more detailed)” [115] Stat:Fit, Stat:Fit Version tutorials, Statistically Fit Program, Geer Mountain Software Corp., South Kent, 2001 [116] Stat:Fit, Stat:Fit Version tutorials, Statistically Fit Program, Geer Mountain Software Corp., South Kent, 2001 [117] L RAMBAUSEK (2008): Table “Operations and their distributions (part 1/3)” [118] L RAMBAUSEK (2008): Table “Operations and their distributions (part 2/3)” Bibliographical references 162 [119] L RAMBAUSEK (2008): Table “Operations and their distributions (part 3/3)” [120] L RAMBAUSEK (2008): Figure “Changing the atoms properties” [121] L RAMBAUSEK (2008): Figure “After a test run of 90 hours the output volume is 7582 units” [122] L RAMBAUSEK (2008): Figure “3D Model View after inserting the atom “VR building” [123] Incontrol Enterprise Dynamics (2008): Figure “Experimentation Wizard” [124] Incontrol Enterprise Dynamics (2008): Figure “Library Tree ED” [125] Incontrol Enterprise Dynamics (2008): Figure “Status Monitor” [126] Incontrol Enterprise Dynamics (2008): Figure “Monitor” [127] Donald Craig (1996): Advantages of Simulation, http://www.cs.mun.ca/~donald/msc/node6.html, Disadvantages of Simulation, http://www.cs.mun.ca/~donald/msc/node7.html (20:53) [128] L GOULD (unknown): Simulation: The Real Story, Gardner Publications Inc., URL: http://www.autofieldguide.com/articles/010202.html (14.6.2008, 15:45) [129] L GOULD (unknown): Simulation: The Real Story, Gardner Publications Inc., URL: http://www.autofieldguide.com/articles/010202.html (14.6.2008, 15:45) [130] THE FEDERATION OF EUROPEAN EMPLOYERS (2008): List of gross minimum wages, FedEE Services Ltd 2008, UK, http://www.fedee.com/minwage.html, Last updated: 23.07.2008, (31.07.2008, 16:49) [131] ISTCOMP (2008): Table “Machinery at ISTCOMP” [132] L RAMBAUSEK (2008): Figure “Machinery at ISTCOMP within the sections I Body and II C&L” [133] L RAMBAUSEK (2008): Figure “Machinery at ISTCOMP within the sections III Sleeve and IV Assembly” [134] Incontrol Enterprise Dynamics (2008), URL: http://www.incontrol.nl/?to=requirements (28.04.2008, 18:25) [135] Incontrol Enterprise Dynamics (2008), URL: http://www.incontrol.nl/?to=requirements, 28.04.2008, 18:25) [136] L RAMBAUSEK (2008): Figure ““Enterprise Dynamics” simulation model layout” [137] L RAMBAUSEK (2008): Figure “”Enterprise Dynamics” simulation model layout with connections” [...]... approach in chapter 9, deals with several line balancing strategies The main subject of this dissertation focuses on line balancing in the context of Lean Manufacturing, avoidance of non-adding value activities and constrains in the usage of simulation software in line balancing in garment production Finally this paper is using SWOT analysis for the application of simulation software in garment manufacturing... in the fourth semester of the study program “European Masters in Advanced Textile Engineering”, organised by the Association of Textile Universities (AUTEX) It will evaluate the use of simulation software application in garment manufacturing industry with special reference to the use in production line balancing The usefulness of simulation software application in the context of line balancing in garment. .. evaluate the use of simulation software in the process of line balancing in garment manufacturing The information is intended to give users or future users of simulation software an overview of strengths and weaknesses in this special case of application Furthermore, this aims to make suggestions concerning possible problem resolutions during the first use of simulation software in line balancing The experimental... manufacturing Another approach to increase productivity is line balancing Line balancing loss is waiting time, which is caused by unbalanced or inadequate balanced production line, expressed in no of operators That means, periods when the operator waits for further work which is coming from workstations in the production line which works in sequential steps If the line is balanced well, the line balancing. .. and constraints of the use of simulation software in the context of line balancing are highlighted Also problems in setting up simulation models in the mentioned context are presented Following aspects will be investigated during the use of the simulation model • output units and productivity, • status of the operator e.g busy or idle, • number of units in inventory, • utility values of the single operations... shift of 8 hours Takt time = 480 minutes 0,96 minutes = 500 units unit The Takt time is 0.96 minutes Every 0.96 minutes one output unit has to be produced to meet production schedule To find the optimum or an appropriate line balancing loss is certainly an issue companies are focussing on Planning tools in production line balancing attract notice of an increasing number of companies To keep the production. .. targets per time If the cycle times of the operations are equal Takt time, the production runs smoothly, if not the line needs to be balanced Line balancing is explained explicit in chapter 6 4.3.1.8 Line balancing Line balancing is a tool for planning the amount of personnel needed for a certain production quantity The various methods for planning are explained in Chapter 6 www.congnhemay.net 17... gained during the research phase in this project The content of this paper deals with the topic production process, touches the matter of line balancing and the theme simulation Results of the empirical part of this work will be given in chapter 9 An overall evaluation of the application in line balancing in garment manufacturing will be discussed in chapter 10 www.congnhemay.net 2 Objectives Aim of this... as in other producing industries, production planning tools are necessary to maintain and to improve productivity which arguably is a competitive advantage In other manufacturing industries, simulation of production processes is well established Simulation is recognized as a powerful problem-solving tool which has its roots in hard systems engineering like car manufacturing In garment and clothing... software in garment manufacturing in chapter 10 Advantages and Disadvantages of the application of simulation software in production line balancing will be addressed Users of the information offered in this thesis should be aware that circumstances of different production sites, of course, change the requirements of the application of the software The improvements within the experiments discussed are