Flexible lot size for kanban system to reduce material overflow in hard disc assembly process

This research was conducted based on a case study at an electronic manufacturing company that produces hard disc. Here, Kitting is the first step in assembly process. It is initiated well before the commencement of actual production to be able to prepare and deliver the material on time. Compound/Ki...

Full description

Saved in:
Bibliographic Details
Main Author: Astuti, Fatma Hermining
Format: Thesis
Language:English
English
Published: 2015
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/16876/1/Flexible%20Lot%20Size%20For%20Kanban%20System%20To%20Reduce%20Material%20Overflow%20In%20Hard%20Disc%20Assembly%20Process.pdf
http://eprints.utem.edu.my/id/eprint/16876/2/Flexible%20lot%20size%20for%20kanban%20system%20to%20reduce%20material%20overflow%20in%20hard%20disc%20assembly%20process.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utem-ep.16876
record_format uketd_dc
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Ebrahim, Zuhriah
topic Q Science (General)
QA Mathematics
spellingShingle Q Science (General)
QA Mathematics
Astuti, Fatma Hermining
Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
description This research was conducted based on a case study at an electronic manufacturing company that produces hard disc. Here, Kitting is the first step in assembly process. It is initiated well before the commencement of actual production to be able to prepare and deliver the material on time. Compound/Kitting section involves the provision of all the materials needed for a particular assembly process from the Warehouse and issuing the materials to the Assembly line. The Compound/Kitting section has been always crowded with high incoming materials (overflow) such that more spaces are needed to allocate the incoming materials. Therefore, the aim of this research is to minimize the overflow of incoming materials at Compound/Kitting section. Thus, three objectives are set: (i) to identify the overflow of incoming material at Compound/Kitting section and its implication to the performance of the subsequent production process, (ii) to analyze the demand changes patterns at production shop floor and its effects to the Compound/Kitting section and Assembly line performances, and (iii) to propose and evaluate the Flexible Lot Size for Kanban System to minimize the overflow of incoming materials. In this regard, Lean Manufacturing tools and techniques such as Value Stream Mapping (VSM) and Kanban system have been adopted to overcome the overflow of incoming materials. The constructed current VSM shows the lack of ordering system and the uncertain changes in demand cause to the overflow of incoming materials. Motivated by these factors, a Flexible Lot Size (FLS) for Kanban System is proposed to resolve the phenomenon. The FLS was modeled using simulation software. It begins by developing the current production simulation model that validated by the historical data of production input and output at Warehouse, Compound/Kitting section and also Assembly line section. In this study, the demand was classified into three categories: low, medium, and high. This research conclude that VSM is an effective tool to map the problems, while the FLS was able to provide the optimum Kanban number and lot size for the case of uncertain demand. In conclusion, a smooth production flow between Warehouse, Compound/Kitting section and Assembly line section can be sustained using the JIT concept “the right quantity at the right time”. In this way, the overflow of incoming materials at Compound/Kitting section has been decreased till 87.3 percent.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Astuti, Fatma Hermining
author_facet Astuti, Fatma Hermining
author_sort Astuti, Fatma Hermining
title Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
title_short Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
title_full Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
title_fullStr Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
title_full_unstemmed Flexible lot size for kanban system to reduce material overflow in hard disc assembly process
title_sort flexible lot size for kanban system to reduce material overflow in hard disc assembly process
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty Of Manufacturing Engineering
publishDate 2015
url http://eprints.utem.edu.my/id/eprint/16876/1/Flexible%20Lot%20Size%20For%20Kanban%20System%20To%20Reduce%20Material%20Overflow%20In%20Hard%20Disc%20Assembly%20Process.pdf
http://eprints.utem.edu.my/id/eprint/16876/2/Flexible%20lot%20size%20for%20kanban%20system%20to%20reduce%20material%20overflow%20in%20hard%20disc%20assembly%20process.pdf
_version_ 1747833905905401856
spelling my-utem-ep.168762022-06-07T13:41:39Z Flexible lot size for kanban system to reduce material overflow in hard disc assembly process 2015 Astuti, Fatma Hermining Q Science (General) QA Mathematics This research was conducted based on a case study at an electronic manufacturing company that produces hard disc. Here, Kitting is the first step in assembly process. It is initiated well before the commencement of actual production to be able to prepare and deliver the material on time. Compound/Kitting section involves the provision of all the materials needed for a particular assembly process from the Warehouse and issuing the materials to the Assembly line. The Compound/Kitting section has been always crowded with high incoming materials (overflow) such that more spaces are needed to allocate the incoming materials. Therefore, the aim of this research is to minimize the overflow of incoming materials at Compound/Kitting section. Thus, three objectives are set: (i) to identify the overflow of incoming material at Compound/Kitting section and its implication to the performance of the subsequent production process, (ii) to analyze the demand changes patterns at production shop floor and its effects to the Compound/Kitting section and Assembly line performances, and (iii) to propose and evaluate the Flexible Lot Size for Kanban System to minimize the overflow of incoming materials. In this regard, Lean Manufacturing tools and techniques such as Value Stream Mapping (VSM) and Kanban system have been adopted to overcome the overflow of incoming materials. The constructed current VSM shows the lack of ordering system and the uncertain changes in demand cause to the overflow of incoming materials. Motivated by these factors, a Flexible Lot Size (FLS) for Kanban System is proposed to resolve the phenomenon. The FLS was modeled using simulation software. It begins by developing the current production simulation model that validated by the historical data of production input and output at Warehouse, Compound/Kitting section and also Assembly line section. In this study, the demand was classified into three categories: low, medium, and high. This research conclude that VSM is an effective tool to map the problems, while the FLS was able to provide the optimum Kanban number and lot size for the case of uncertain demand. In conclusion, a smooth production flow between Warehouse, Compound/Kitting section and Assembly line section can be sustained using the JIT concept “the right quantity at the right time”. In this way, the overflow of incoming materials at Compound/Kitting section has been decreased till 87.3 percent. 2015 Thesis http://eprints.utem.edu.my/id/eprint/16876/ http://eprints.utem.edu.my/id/eprint/16876/1/Flexible%20Lot%20Size%20For%20Kanban%20System%20To%20Reduce%20Material%20Overflow%20In%20Hard%20Disc%20Assembly%20Process.pdf text en public http://eprints.utem.edu.my/id/eprint/16876/2/Flexible%20lot%20size%20for%20kanban%20system%20to%20reduce%20material%20overflow%20in%20hard%20disc%20assembly%20process.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96136 mphil masters Universiti Teknikal Malaysia Melaka Faculty Of Manufacturing Engineering Ebrahim, Zuhriah 1. Abdulmalek, F.A., and Rajgopal, J., 2007. Analyzing The Benefits of Lean Manufacturing and Value Stream Mapping Via Simulation: A Process Sector Case Study. International Journal of Production Economics, 107 (1), pp. 223–236. 2. Aghajani, M., Keramati, A., and Javadi, B., 2012. Determination of Number of Kanban In a Cellular Manufacturing System with Considering Rework Process. International Journal of Advance Manufacturing Technology, 63 (9-12), pp. 1177–1189. 3. Al-khafaji, S.K.H., and Al-Rufaifi, H.M.R., 2012. A Case Study of Production Improvement by Using Lean with Simulation Modeling. Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management. 3rd– 5th July. Istanbul, Turkey, pp. 271–279. 4. Álvarez, R., Calvo, R., Peña, M.M., and Domingo, R., 2008. Redesigning an Assembly Line Through Lean Manufacturing Tools. International Journal of Advance Manufturing Technology, 43(1), pp. 949–958. 5. Azadeh, A., Ebrahimipour, V., and Bavar, P., 2010. A Hybrid GA-simulation Approach to Improve JIT Systems. International Journal of Production Research, 48(8), pp. 2323–2344. 6. Banks, J., Carson, J.S., Nelson, L.B., and Nicol, D.M., 2010. Discrete Event System Simulation, 5th ed., New Jersey: Prentice-Hall. 7. Benson, D., 1997. Simulation Modeling and Optimization Using ProModel. In: Proceedings of the 1997 Winter Simulation Conference, pp. 587–593. 8. Berkley, J.B., 1992. A Review of the Kanban Production Control Research Literature. Production and Operation Management, 1 (4), pp. 393–411. 9. Bhat, R.R., and Shivakumar, P.S., 2011. Improving the Productivity using Value Stream Mapping and Kanban Approach. International Journal of Scientific & Engineering Research, 2 (8), pp. 1–5. 10. Bhasin, S., and Burcher, P., 2006. Lean Viewed as a Philosophy. Journal of Manufacturing Technology Management. 17 (1), pp. 56–72. 11. Bicheno, J., 2004. The New Lean Toolbox: Towards Fast, Flexible Flow, 5th ed., UK : Picsie. 12. Brunt, D., 2000. From Current State to Future State: Mapping the Steel to Component Supply Chain. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, 3 (3), pp. 259–271. 13. Carnevalli, J. A., and Miguel, P.C., 2008. Review, Analysis and Classification of the Literature on QFD—Types of Research, Difficulties and Benefits. International Journal of Production Economics. 114 (2), pp. 737–754. 14. Carreira, B., 2005. Lean Manufacturing That Works: Powerful Tools for Dramatically Reducing Waste and Maximising Profits. New York : Broadway. 15. Chase, R ., Jacobs, F., and Aquilano, N.J., 2006. Operations Management for Competitive Advantage, 11th ed. New York : McGraw-Hill 16. Chong, K.E., 2012. Simulation Approach for Improving Throughput and Cycle Time for High Precision Component Manufacturing Industry. PJP Report. University Teknikal Malaysia Melaka. 17. Comm, C.L., and Mathaisel, D.F.., 2005. An Exploratory Analysis in Applying Lean Manufacturing to a Labor-Intensive Industry in China. Asia Pacific Journal of Marketting and Logistic, 17(4), pp. 63–80. 18. Cooper, D.R., and Schindler, P.S., 2006. Business Research Methods, 9th ed. New York : McGraw-Hill. 19. Detty, R., and Yingling, J., 2000. Quantifying Benefits of Conversion to Lean Manufacturing with Discreate Event Simulation: a Case Study. International Journal of Production Research, 38 (2), pp. 429–445. 20. Duanmu, J., and Taaffe, K., 2007. Measuring Manufacturing Throughput Using Takt Time Analysis and Simulation. Proceedings of the 2007 Winter Simulation Conference. 9th-12th Dec. Washington, DC, USA, pp. 1633–1640. 21. Emde, S., Boysen, N., 2012. Optimally Locating In-House Logistics Areas to Facilitate JIT-Supply of Mixed-Model Assembly Lines. International Journal of Production Economics, 135 (1), pp. 393–402. 22. Emiliani, M., and Stec, D., 2004. Using Value-Stream Maps to Improve Leadership. The Leadership and Organisation Development Journal. 25 (8), pp. 622–645. 23. Feld, W., 2001. Lean Manufacturing: Tools, Techniques, and How to Use Them, Boca Raton : St. Lucie Press. 24. Framinan, J., Gonzales, P., and Ruiz-Uzano, R., 2006. Dynamic Card Controlling in a Conwip System. International Journal of Production Economics. 99 (1-2), pp. 102–116. 25. Gaither, N., and Frazier, G., 2002. Operations Management, 9th ed. SouthWestern: Mason,OH. 26. Gershwin, S.B., 2000. Design and Operation of Manufacturing Systems. IIE Transaction. 32 (2), pp. 93–103. 27. Gupta, S.M., Al-Turki, Y.A.Y., and Perry, R.F., 1999. Flexible Kanban System. International Journal of Operation Production Management, 19 (10), pp.1065–1093. 28. Gurumurthy, A., Kodali, R., 2011. Design of Lean Manufacturing Systems Using Value Stream Mapping with Simulation: a Case Study. Journal of Manufacturing Technology Management, 22 (4), pp. 444–473. 29. Harrell, C., Ghosh, B.K., and Bowden, R.O., 2004. Simulation using ProModel, 2nd ed. Boston:McGraw-Hill/Higher Education. 30. Hall, R.W., 1983. Zero Inventories Crusade – Much More than Materials Management. Production and Inventory Management Journal. 24 (3), pp. 1–8. 31. Heizer, J., and Render, B., 2006. Operation Management, 8th ed. NJ: Pearson/Prentice Hall. 32. Helo, P., 2004. Managing Agility and Productivity in the Electronics Industry. Industrial Management & Data System. 104 (7), pp. 567–577. 33. Hemamalini, B., and Chandrasekharan, R., 2000. Determination of the Number of Containers, Production Kanbans and Withdrawal Kanbans; and Scheduling in Kanban Flowshops. International Journal of Production Research, 38 (11), pp. 2529–254. 34. Hines, P., Holweg, M., and Rich, N., 2004. Learning to evolve: A review of contemporary lean thinking. International Journal of Operations & Production Management, 24(10), pp. 994–1011 35. Holweg, M., 2007. The Genealogy of Lean Production. Journal of Operations Management, 25 (2), pp. 420–437. 36. Hopp, W.J., Spearman, M.L., 2001. Factory Physics, 2nd ed. ed. New York : McGraw-Hill. 37. Hopp, W.J., and Spearman, M.L., 2004. To pull or not to pull: What is the questions?. Manufacturing and Service Operations Management, 6 (2), pp.133-148 38. Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L.K., and Young, T., 2010. Simulation in Manufacturing and Business: A review. European Journal of Operational Research. 203 (1), pp. 1–13. 39. Karlsson, C., and Ahlstrom, P., 1996. Assessing Changes towards Lean Production. International Journal of Operations and Production Management. 16 (2), pp. 24–41. 40. Karmarkar, U.S., and Kekre, S., 1989. Batching Policy in Kanban systems. Journal of Manufacturing System. 8 (4), pp. 317–328. 41. Kelton, W.D., Sadowski, R., and Sadowski, D., 2002. Simulation with Arena, 2nd ed. New York:McGraw-Hill. 42. Kevin, J., 2005. ProModel Help System. 43. Khanna, R.B., 2007. Productivity and Operations Management. New Delhi : PHI Learning Private Limited. 44. Kolich, D., Storch, R.L., and Fafandjel, N., 2012. Value Stream Mapping Methodology for Pre-Assembly Steel Process in Shipbuilding. International Conference on Innovative Technologies (IN-TECH). 10th-13th Sept. Budapest, Hungary, pp. 365–368. 45. Koumanakos, D., 2008. The Effect of Inventory Management on Firm Performance. International Journal of Productivity and Performance Management. 57(5), pp.355–369. 46. Kumar, C.S., Panneerselvam, R., 2007. Literature review of JIT-KANBAN System. The International Journal of Advanced Manufacturing Technology, 32 (3-4), pp. 393–408. 47. Law, A.M., 2007. Simulation Modelling and Analysis. 4th ed. NY: McGraw-Hill. 48. Lee, I., 2007. Evaluating Artificial Intelligence Heuristics for a Flexible Kanban System : Simulataneous Kanban Controlling and Schedulling. International Journal of Production Research. 45 (13), pp. 2859–2873. 49. Lee-Mortimer, A. 2008. A continuing lean journey: an electronic manufacturer’s adopting of Kanban, Assembly Automation, 28(2), pp. 103-112 50. Lian, Y., and Landeghem, H. Van., 2007. Analyzing the Effects of Lean Manufacturing using a Value Stream Mapping based Simulation Generator. International Journal of Production Research, 45 (13), pp. 3037–3058. 51. Lian, Y., and Landeghem, H. Van., 2002. An Application of Simulation and Value Stream Mapping in Lean Manufacturing. Proceeding 14th European Simulation Symposium. 23rd-26th Oct. Dresden, Germany, pp. 300-307 52. Liker, J.K., 2004. The Toyota Way: 14 Management Principles From The World’s Greatest Manufacturer. New York : McGraw-Hill. 53. Littlefield, M., Roberts, M., 2012. Achieving Operational Excellence in Electronics Manufacturing. [online] Available at: www.lnsresearch.com [Accessed on July 2012] 54. Locher, D.A., 2008. Value Stream Mapping for Lean Development : A How-To Guide for Streamlining Time to Market. NY : Productivity Press. 55. Lovelle, J., 2001. Mapping the Value Stream – Use Value Stream Mapping to Reveal the Benefits of Lean manufacturing. IIE Solution. 33(2), pp. 26–33. 56. Lummus, R., 1995. A Simulation Analysis of Sequencing Alternatives for JIT Lines Using Kanbans. Journal of Operations Management. 13, pp. 183–191. 57. Mcdonald, T., Aken, E.M.V., and Rentes, A.F., 2002. Utilising Simulation to Enhance Value Stream Mapping : A Manufacturing Case Application. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management. 5 (2), pp. 213–232. 58. Melton, T., 2005. The Benefits of Lean Manufacturing : What Lean Thinking has to Offer the Process Industries. Chemical Engineering Research and Design. 83 (6), pp. 662–673. 59. Miltenburg, J., 2007. Level Schedules for Mixed-Model JIT Production Lines: Characteristics of the Largest Instances that can be Solved Optimally. International Journal of Production Research, 45 (16), pp. 3555–3577. 60. Monden, Y., 1983. The Toyota Production System. Portland: Productivity Press. 61. Monden, Y., 1998. Toyota Production System-an Integrated Approach to Just In Time. Georgia:Engineering and Management Press. 62. Muthiah, K.M.., and Huang, S.H., 2006. A review of literature on manufacturing systems productivity measurement and improvement. International Journal of Industrial and Systems Engineering. 1(4) , pp. 461-484. 63. Nandikolmath, T., Pareek, P.K., and Vasantha Kumara S A,. 2012. Implementation of a Lean Model for Carrying Out Value Stream Mapping in a Manufacturing Industry, International Journal of Mechanical Engineering and Robotics Research, 1 (2), pp. 88–95. 64. Ohno, T., 1988. Toyota Production System. Cambridge, MA : Productivity Press. 65. Pasqualini, F., and Zawislak, P.A., 2005. Value Stream Mapping in Construction: A Case Study in a Brazilian Construction Company. In: 13th International Group for Lean Construction Conference: Proceedings. pp. 117–125. 66. Peterson, J., and Smith, R., 1998. The 5S Pocket Guide. Portland : Productivity Inc. 67. Pisuchpen, R., 2012. Integration of JIT Flexible Manufacturing, Assembly and Disassembly Using a Simulation Approach. International Journal of Industrial and Systems Engineering. 32 (1), pp. 51–61. 68. ProModel Corporation, 2002. SimRunner User Guide. 69. Rahani, A.R., and Al-Ashraf, M., 2012. Production Flow Analysis through Value Stream Mapping: A Lean Manufacturing Process Case Study. Procedia Engineering, 41, pp. 1727–1734. 70. Ranko, B., Borislav, G., and Dragan, M., 2006. Lean Concept in a Supply Chain. In: 10th International Research/Expert Conference “Trends in the Development of Machinery and Associated Technology”. 11th-15th Sept. Barcelona, Spain, pp. 1383–1386. 71. Reesa, L.P., Philipoomb, P.R., Taylor, B.W., and Huanga, P.Y., 1987. Dynamically Adjusting the Number of Kanbans in a Just-in-Time Production System Using Estimated Values of Leadtime. IIE Transaction, 19 (2), pp. 199–207. 72. ReVelle, J.B., 2002. Manufacturing Handbook of Best Practices: An Innovation, Productivity and Quality Focus. Florida : CRC Press LLC. 73. Robinson, S., 2004. Simulation: The Practice of Model Development and Use. UK : Wiley, Chichester. 74. Rother, M., and Shook, J., 1999. Learning to see. MA: Lean Enterprise Institute Inc. 75. Santos, J., Wysk, R., and Torres, J., 2006. Improving Production with Lean Thinking. New Jersey : John Wiley and Sons. 76. Sargent, R.G., 2010. Verification and Validation of Simulation Models. In: Proceedings of the 2010 Winter Simulation Conference. 5th- 8th Dec. Baltimore, MD, pp. 166–183. 77. Schroeder, R.G., 2007. Operations Management: Contemporary Concepts and Cases. 3rd edition. New York : McGraw-Hill. 78. Sekaran, U., 2006. Research Methods for Business. NY: John Wiley and Sons. 79. Seth, D., Gupta, V., 2005. Application of Value Stream Mapping for Lean Operations and Cycle Time Reduction: an Indian Case Study. Journal of Production Planning & Control. 16(1), pp. 44–59. 80. Shahabudeen, P., and Sivakumar, G.D., 2008. Algorithm for the design of single-stage adaptive kanban system. Computers and Industrial Engineering. 54 (4), pp. 800–820. 81. Shingo, S., 1988. Zero Quality Control : Sources Inspection and the Poka-Yoke System. Portland : Productivity Press. 82. Shingo, S., 1989. A Study of the Toyota Production System, revised edition. Cambridge, MA : Productivity Press. 83. Singh, B., Garg, S.K., Sharma, S.K., and Grewal, C., 2010. Lean Implementation and Its Benefits to Production Industry. International Journal of Lean Six Sigma, 1 (2), pp. 157–168. 84. Srisuwanrat, C., G.Ioannou, P., and Tsimhoni, O., 2008. Simulation and Optimization for Construction Repetitive Projects Using ProModel and Simrunner. In: Proceedings of the 2008 Winter Simulation Conference, 7th – 10th Dec. Miami, FL, pp. 2402–2412. 85. Sundar, R., Balaji, a. N., & Kumar, R. M. S., 2014. A Review on Lean Manufacturing Implementation Techniques. Procedia Engineering, 97, pp. 1875–1885. 86. Sugimori, Y., Kusunoki, K., Cho, F., and Uchikawa, S., 1977. Toyota Production System and Kanban System Materialization of Just-In-Time and Respect for Human System. International Journal of Production Research, 15(6), pp. 553–564. 87. Taj, S., and Morosan, C., 2011. The Impact of Lean Operations on the Chinese Manufacturing Performance. Journal of Manufacturing Technology Management, 22 (2), pp. 223–240. 88. Takahashi, K., and Nakamura, N., 1988. Ordering Alternatives in JIT Production Systems. Production Planning and Control: The Management of Operations, 9(8), pp. 784–794. 89. Tapping, D., Luyster, T., Shuker, T., 2002. Value Stream Management: Eight Steps to Planning, Mapping, and Sustaining Lean Improvements. New York : Productivity Press. 90. Tardif, V., Maaseidvaag, L., 2001. An Adaptive Approach to Controlling Kanban Systems. European Journal of Operational Research, 132 (2), pp. 411–424. 91. Thomas, B., Hammel, U., and Schwefel, H., 1997. Evolutionary Computation : Comments on the History and Current State. IEEE Transactions on Evolutionary Computation,1 (1), pp. 3–17. 92. Triola, M.F., 2008. Elementary Statistic : With Multimedia Study Guide, 10th ed. MA : Pearson. 93. Verdi, F., 2008. Lean Manufacturing for Electronics [online] Available at : http://www.empf.org [Accessed on 2 March 2013]. 94. Wilson, L., 2010. How to Implement Lean Manufacturing. USA : McGraw-Hill. 95. Womack, J., 2006. Value Stream Mapping. Manufacturing Engineering Magazine, May, pp. 136. 96. Womack, J.P., Jones, D.T., and Roos, D., 1996. The Machine that Changed the World. New York : Macmillan. 97. Womack, J.P. and Jones, D.T., 2003. Lean Thinking: Banish Waste and Create Wealth In Your Corporation. New York : Simon & Schuster. 98. Zylstra, K.D., 2006. Lean Distribution: Applying Lean Manufacturing to Distribution, Logistics, and Supply Chain. New Jersey : John Wiley and Sons.