IMPROVING WORK IN PROCESS QUALITY (BIAS CUTTING PROCESS) BY USING POKA-YOKE AND DEFINE MEASURE ANALYSIS IMPROVE AND
CONTROL (DMAIC) METHOD IN LEADING MOTORCYCLE TIRE MANUFACTURING
By Budy Ariyanto
21952019
MASTER’S DEGREE in
MASTER OF MECHANICAL ENGINEERING – ENGINEERING MANAGEMENT
FACULTY OF ENGINEERING AND INFORMATION TECHNOLOGY
SWISS GERMAN UNIVERSITY The Prominence Tower
Jalan Jalur Sutera Barat No. 15, Alam Sutera Tangerang, Banten 15143 - Indonesia
February 2021
Revision after Thesis Defense on January 25, 2021
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Budy Ariyanto STATEMENT BY THE AUTHOR
I hereby declare that this submission is my own work and to the best of my knowledge, it contains no material previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at any educational institution, except where due acknowledgement is made in the thesis.
Budy Ariyanto, S.T
____________________________________________
Student Date
Approved by:
Dr. Eng. Sumarsono, S.T., M.T.
____________________________________________
Thesis Advisor Date
Dr. Tanika D. Sofianti, S.T., M.T.
____________________________________________
Thesis Co-Advisor Date
Dr. Maulahikmah Galinium, S. Kom., M.Sc.
____________________________________________
Dean
Date Revision after Thesis Defense on January 25, 2021
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Budy Ariyanto ABSTRACT
IMPROVING WORK IN PROCESS QUALITY (BIAS CUTTING PROCESS) BY USING POKA-YOKE AND DEFINE MEASURE ANALYSIS IMPROVE
CONTROL (DMAIC) METHOD IN LEADING MOTORCYCLE TIRE MANUFACTURING
By
Budy Ariyanto, S.T
Dr. Eng. Sumarsono, S.T., M.T., Advisor Dr. Tanika D. Sofianti, S.T., M.T., Co-Advisor
SWISS GERMAN UNIVERSITY
The leading tire manufacturing has a cost of poor quality on scrap work in process and Rework. Cost of Poor Quality on scrap work in process has a 90% contribution to the total rejected of products. Nylon scrap is one part of in-process scrap work, which dominates the overall scrap work in process. In nylon scrap, there is a type of scrap, namely avoid condition which contributes 74% of total nylon scrap. This research was conducted which aims to improve quality by minimizing nylon scrap. The method used to reduce nylon scrap is the DMAIC approach and Poka yoke design. The Improvement of the Scrap Work in Process by Using action plan 5W + 1H and designing method of DMAIC & Poka yoke design can be shown the data of scrap decreased 26% for Scrap Out spec quality and 68% for return from next process. The analysis of economy impacted outlook of payback period are 0.06 month and 1.05 month. The result in a reduction scrap nylon resulting in a value from 5880 PPM to 3454 PPM by maximum target 4270 PPM.
Keywords: Poka-Yoke, DMAIC, 5W+1H, Payback Period, Nylon Scrap
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Budy Ariyanto
© Copyright 2021 By Budy Ariyanto All rights reserved
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Budy Ariyanto DEDICATION
This thesis is dedicated to the Indonesian country and the improvement of the company where I work, so that it can continue to compete in local and international
markets.
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Budy Ariyanto ACKNOWLEDGEMENTS
Praise and gratitude for Allah Subhanahuwata 'ala thanks to His grace and grace so that the author can compile a thesis entitled "Improving Work In Process Quality (Bias Cutting Process) By Using Poka-Yoke And Dmaic Method In Leading Motorcycle Tire Manufacturing". This thesis was made and can be completed by the assistance of several parties, namely as follows:
1. Beloved mother who has provided moral support and has provided motivation for the author to carry out this Final Project research;
2. Ani Anica Januarti.SE and Umair zuhud asshidiq, beloved wife and children who have provided moral support and motivation in completing this thesis
3. Dr. Ita Mariza, as the Director of the Gajah Tunggal Polytechnic who has fought for and facilitated writers to continue their education.
4. Dr. Eng. Sumarsono Sudarto, S.T., M.T., as advisor who has motivated and directed to finish the study well and has guided me during the process of completing this thesis.
5. Dr. Tanika D. Sofianti, S.T., M.T., as Co-advisor who has motivated and directed to finish the study well and has guided me during the process of completing this thesis.
6. All Leaders at PT GT and my collegues at PT GT For Their Support and Understanding during my research
7. Dr. Ir. Gembong Baskoro, M.sc as SGU's Strategic Development and Cooperation Director who always provides motivation and education.
8. Dena Hendriana, B.Sc., S.M., Sc.D as Dean of the Faculty of Engineering and Information Technology at Swiss German University who has streamlined the thesis writing process.
9. Swiss German University student friends who always support and encourage each other from the beginning to the end of the lecture period
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Budy Ariyanto TABLE OF CONTENT
Page
STATEMENT BY THE AUTHOR ... 2
ABSTRACT ... 3
DEDICATION... 5
ACKNOWLEDGEMENTS ... 6
TABLE OF CONTENT ... 7
LIST OF FIGURES ... 10
LIST OF TABLES ... 11
CHAPTER 1 - INTRODUCTION ... 12
1.1. Background ... 12
1.2. Research Problems ... 14
1.3. Research Objectives ... 14
1.4. Significance of Study ... 14
1.5. Research Questions ... 14
1.6. Scope Limitations ... 14
CHAPTER 2 – LITERATURE REVIEW ... 15
2.1. Flow of Research ... 15
2.2. Previous Research ... 16
2.3. Consideration Determine Method ... 17
2.3. Work in Process ... 19
2.4. Six Sigma ... 19
2.5. Define Measurement Analysis Improve and Control (DMAIC) ... 19
2.6. Fish Bone Diagram ... 22
2.7. Pareto Diagram ... 23
2.8. Statistic of Six Sigma ... 24
2.9. Flow Chart ... 26
2.10. Payback Period... 27
2.11. Control Chart ... 27
2.12. Tree Diagram / Task Diagram ... 28
2.13. Normality Test (The Kolmogorov-Smirnov) ... 28
2.14. Paired T - Test ... 29
2.15. Poka - Yoke... 30
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Budy Ariyanto
2.16. 5W + 1H ... 32
2.17. Bias Cutting ( Ply/ Nylon Product) ... 33
2.18. Quality... 34
CHAPTER 3 – RESEARCH METODOLOGY ... 36
3.1. Scope of Study ... 36
3.2. Time Frame of Study... 36
3.3. Research Process/Research Framework ... 37
3.4. Population and Sampling Method ... 38
3.5. Method of Analysis ... 38
CHAPTER 4 – RESULT AND ANALYSIS ... 39
4.1. Define ... 39
4.2. Measurement ... 40
4.3. Measure of CTQ (Critical to Quality) ... 43
4.4. Analysis of Scrap out Specification & Failure Process ... 44
4.5. Improvement out Specification and Process Failure ... 53
4.6. Analysis of Scrap Return from Next Process ... 55
4.7. Improvement of Scrap Return from Next Process ... 65
4.8. Control by Evaluation of Before and After Improvement ... 67
4.9. Control by Standardization ... 69
4.8. Cost Analysis of Improvement ... 70
CHAPTER 5 – CONCLUSION ... 75
5.1. Conclusion & Finding ... 75
5.2. Recommendation for Company ... 75
5.3. Recommendation for Study ... 76
REFERENCE ... 77
APPENDIX 1 ... 80
APPENDIX 2 ... 81
APPENDIX 3 ... 82
APPENDIX 4 ... 83
APPENDIX 5 ... 84
APPENDIX 6 ... 85
APPENDIX 7 ... 86
APPENDIX 8 ... 87
APPENDIX 9 ... 88
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Budy Ariyanto
APPENDIX 10 ... 89
APPENDIX 11 ... 90
APPENDIX 12 ... 91
CURRICULUM VITAE ... 92
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Budy Ariyanto LIST OF FIGURES
Figures Page
Figure 1. 1. Actual Scrap VS Target Company ... 13
Figure 2. 1. Mind Map Research ... 15
Figure 2. 2. DMAIC Flow Process ... 22
Figure 2. 3. Distribution of Normal ... 29
Figure3. 1. Flow chart Research Methodology ... 37
Figure4. 1 Avoid & un-Avoid Scrap... 39
Figure 4. 2. P – Chart Diagram ... 42
Figure4. 3. Target VS Actual Scrap ... 43
Figure 4. 4. Critical to Quality ... 43
Figure4. 5. Scheme Bias Cutting Machine ... 45
Figure 4. 6. Flow Chart Bias Cutting Process ... 45
Figure 4. 7. Pareto Diagram out Specification & Failure Process per Machine ... 47
Figure4. 8. Fishbone Diagram out Specification & Failure Process... 47
Figure 4. 9. Schema Scrap of Return from Next Process ... 55
Figure 4. 10. Scrap Return from Next Process ... 55
Figure 4. 11. Interrelationship of Scrap Return from Next Process... 56
Figure 4. 12. Pareto Diagram of Scrap from next process ... 57
Figure 4. 13. Tree Task Diagram Bias cutting Process... 58
Figure 4. 14. Fishbone Diagram Width Over/Under ... 60
Figure 4. 15. Fishbone Diagram Bad Winding ... 61
Figure 4. 16. Fishbone Thickness Over/Under ... 62
Figure 4. 16. Before & after (data sampling of Scrap) ... 67
Figure 4. 18. Before After Sampling Item Error ... 68 Figure 4. 19. Proportional reduction scrap based on average data scrap (2018-2020) 69
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Budy Ariyanto LIST OF TABLES
Tables Pages
Table 2. 1. Previous Researches ... 16
Table 2. 2. Pros and Cons Quality Improvement Method ... 18
Table 2. 3. Sigma Level and DPMO ... 25
Table 2. 4. Function of Flow Chart ... 26
Table 2. 5. 5W +1H ... 33
Table 4. 1. Categories Avoid & Un-Avoid Scrap. ... 39
Table 4. 2. Sigma Level ... 40
Table 4. 3. Sigma Classification ... 41
Table 4. 4. Scrap out Specification & Failure Process per Machine ... 46
Table 4. 5. Root Cause Analysis ... 48
Table 4. 6. 5W + 1H Out Specification and Failure Process Machine 03 ... 49
Table 4. 7. Sample of Data Before and After Scrap (ppm) ... 50
Table 4. 8. Normality Test ... 50
Table 4. 9. Paired t – test Home Brake Before & after. ... 51
Table 4. 10. Paired t – test Rell Cutter Before & after. ... 51
Table 4. 11. Paired t – test Selection & Changing Material ... 51
Table 4. 12. Result of Hypothesis ... 52
Table 4. 13. Improvement Adding Spring ... 53
Table 4. 14. Handling Reduced Scrap ... 54
Table 4. 15. Systematic Process and Error Description ... 59
Table 4. 16. Percentage of Error ... 63
Table 4. 17. Improvement Plan 5W + 1H ... 64
Table 4. 18. Improvement Sheet Scrap Width Over/Under ... 65
Table 4. 19. Improvement Sheet of Lock Shaft ... 66
Table 4. 20. Improvement Sheet of Thickness Gauge ... 66
Table 4. 21. Before & After Improvement ... 67
Table 4. 22. Before & after Improvement of Scrap Return from Next Process ... 68
Table 4. 23. Standardization of Improvement ... 69
Table 4. 24. Payback Period Improvement of Scrap out ... 70
Table 4. 25. Payback Period Improvement of Scrap Return From Next Process ... 72
