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In Process Kanban Optimization for a Manufacturing Simulation
Technical Paper
2013-01-0065
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Identifying and investigating the need for optimal In Process Kanbans (IPKs) for a complex manufacturing environment is the need of the time. Multiple simulations are required to arrive at the number of Kanbans required and the amount of part quantities it needs to store to achieve maximum throughput. In house developed tool is used to simulate the manufacturing system. The tool works on exhaustive search optimization algorithm to maximize the throughput of the manufacturing system by maintaining the minimum cost of the system. The location and size of the IPK is optimized using this tool. Since no analytical solution is possible we use optimization algorithms in conjunction with the simulation tool. We demonstrate our approach in this paper with the help of a case study. We observe with regards to the case study, that the optimal location of the IPK is vital to achieve maximum throughput as compared to the optimal size of the IPK.
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Pingle, A., Sabnis, S., and Pandey, G., "In Process Kanban Optimization for a Manufacturing Simulation," SAE Technical Paper 2013-01-0065, 2013, https://doi.org/10.4271/2013-01-0065.Also In
References
- Ashburn , A. 1986 Toyota famous Oh No system, American machinist Monden Y. Applying Just in Time: The American/Japanese Experience IIE Press
- Monden , Y. 1983 The Toyota Production System Industrial Engineering and Management Press Nocross, GA
- Hong , L. J. , and Nelson B. L. 2009 A Brief Introduction to Optimization via Simulation Proceedings of the 2009 Winter Simulation Conference Rossetti M. D. , Hill R. R. , Johansson B. , Dunkin A. , and Ingalls R. G. 75 84 Piscataway, New Jersey Institute of Electrical and Electronics Engineers, Inc.
- Gürkan , G. 2000 Simulation Optimization of Buffer Allocations in Production Lines with Unreliable Machines Annals of Operations Research 3 1-4 177 216
- Di Mascolo , M. , Frein Y. , Dallery Y. & David R. 1991 A unified modeling of kanban systems using petri nets Intl. Journal of Flexible Manufacturing Systems 3 275 307
- Glasserman , P. & Yao David 1994 A GSMP framework for the analysis of production lines Yao D. Stochastic Modeling and Analysis of Manufacturing Systems Springer-Verlag 133 188
- Wang Shaojun , Koch Doug & Ren Yifeng 2008 A Hands-on Kanban Simulation Kit for Lean Manufacturing IAJC-IJME International Conference 978-1-60643-379-9
- Selvaraj N. 2009 The Optimization of Number of Kanbans in GKCS with Simulation Technique ARPN Journal of Engineering and Applied Sciences 4 5 44 52
- Chaharsooghi S.K. , Sajedinejad A. 2010 Determiniation of the Number of Kanbans and Batch Sizes in a JIT Supply Chain System Transaction E: Industrial Engineering 17 2 143 149
- Rekiek Brahim , Delchambre A. Assembly Line Design: The Balancing of Mixed-model Hybrid Lines with Genetic Algorithms
- Faria Jose , Matos Manuel , Nunes Eusebio Optimal design of work-in-process buffers International Journal of Production Economics 99 1-2 January February 2006 144 155