Abstract
Material handling is a loose loop in most assembly plants. Just-in-time (JIT) is a management philosophy that strives to eliminate sources of manufacturing waste by producing the right part in the right place at the right time. We propose to apply JIT principles to material handling in assembly plants. Material Kanbans are introduced as an effective means to control and balance the physical material/part flow in the plant floor. An agent-based simulation prototype is implemented using Anylogic™. The flexibility of the agent-based approach, facilitates the simulation of various “what-if” scenarios including different layout designs, objective parameters and dynamic situations in the plant floor.
Keywords
- Assembly Line
- Material Handling
- Material Handling System
- Material Requirement Planning
- Plant Floor
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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6. References
Askin, RG. Manual and operator-based transfer batch sizes in JIT mani~facturing. In Proceedings of Promat’99, Chicago, IL, pp.1–21. 1999. Reprinted in Progress in Material Handling Practice: 1999, Material Handling Institute, Charlotte, NC, pp. 167–87.
Berkley, BJ. A review of Kanban production control research literatore, Prodaction and Operations Management 1992; l(4): 393–411
Gupta: SM and Al-Turki, YAY. The effect of sodden material handling system breakdown on the performance of a JIT system. International Journal of Production Research 1998; 36(7):1935–60.
Hao, Q, Shen, W, Zhang, Z, An Autonomous Agent Development Environment for Engineering Applications, International Journal of Advanced Engineering Informatics, 2005. 19(2):123–134.
Hopp, W and Spearman, M. Factory Physics: Foundations of Factory Management. InvinIMcGraw Hill, Chicago, IL, 1996.
Krishnamurthy, A, Suri, R and Vernon, M. Re-examining the performance of MRP and Kanban material control strategies for multi-product flexible manufacturing systems. International Journal of Flexible Manufacturing Systems 2004; 16(2):123–50.
Kusiak Andrew. Computational Intelligence in Design and Manofacturing. John-Wiley &Sons, Inc., 2000.
Martins, K and Lewandrowski. U. Inventory safety stocks of kanban control systems. Production Planning and Control 1999; 10(6):520–29.
Shen, W, Norrie, DH and Barthes. JP. Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing. Taylor and Francis, London, UK, 2001.
Shirk, WT. Material flow controls in a JIT environment. In Proceedings of the Technical Program: Kational Electronic Packing and Production Conference (NEPCOK EAST’88), pp.325–332. 1988.
Smith, RG. The Contract Net Protocol: high-level commi~nication and control in a distributed problem solver. IEEE Transactions on System, Man, and Cybernetics 1980: C-29(12): 1104–13.
Uzsoy. R, Martin-Vega, LA. Modelling Kanban-based demand-pull systems: a survey and critique. Manufacturing Review 1990; 3(3): 155–60.
Venkataramanaiah, S, Krishnaiah, K and Pichandi, R. Management of WIP inventory in JIT environment under cellular layout-a case study. Journal of Scientific &Industrial Research 2001; 60(3):256–63.
Womack, JP and Jones, DT. Lean Thinking: Banish Waste and Create Wealth in Your Corporation. Simon and Schuster, New York, NY, 1996.
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© 2006 International Federation for Information Processing
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Hao, Q., Shen, W. (2006). An Agent-Based Simulation of A Jit Material Handling System. In: Information Technology For Balanced Manufacturing Systems. BASYS 2006. IFIP International Federation for Information Processing, vol 220. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-36594-7_8
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DOI: https://doi.org/10.1007/978-0-387-36594-7_8
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-36590-9
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