توسعه مدل شبیه سازی برای ارزیابی سیستم کانبان تعمیم یافته با سیاست تنظیم پویای تعداد کانبان‌ها

نوع مقاله: پژوهشی

نویسندگان

1 دانشگاه تربیت مدرس

2 پژوهشگاه علوم و فناوری اطلاعات ایران

چکیده

سیستم‌های کانبان یکی از راهکارهای موثر کنترل موجودی در سیستم‌های تولید به‌هنگام هستند. ارزیابی سیستم کانبان که بر اساس مکانیزم کنترل جریان مواد تعریف شده و مقدار و زمان مناسب تولید محصولات را کنترل می‌کند، از اهمیت به‌سزایی برخوردار است. در این مقاله، روشی جدید برای تنظیم پویای تعداد کانبان‌ها در هر مرحله با توجه به مقدار تقاضای پس‌افت در ایستگاه آخر ارائه شده است. از جمله مزایای روش پیشنهادی، سادگی تنظیم پارامترهای روش است. برای تعیین تعداد کانبان‌ها و ارزیابی روش پیشنهادی در سیستم‌ کانبان تعمیم‌یافته، یک مدل شبیه‌سازی ارائه شده است. تاثیر تغییر پویای تعداد کانبان‌ها، روی شاخص‌های متوسط میزان تولید، متوسط موجودی نیم‌ساخته، متوسط زمان تولید یک محصول و نرخ بهره‌وری ماشین‌آلات بررسی شده است. از مدل شبیه‌سازی جهت بررسی تخصیص غیریکسان کانبان‌ها به مراحل مختلف تولید نیز استفاده شده است. نتایج شبیه‌سازی نشان می‌دهد که بکارگیری سیاست پیشنهادی تنظیم پویای تعداد کانبان‌ها در سیستم کانبان تعمیم‌یافته و تعیین مناسب پارامترها در طول فرآیند تولید می‌تواند افزایش نرخ تولید و کاهش تقاضای پس افت را در مقایسه با روش‌های موجود به همراه داشته باشد.

کلیدواژه‌ها


عنوان مقاله [English]

A Simulation Model for dynamically adjusting the number of Kanbans in Generalized Kanban Systems

چکیده [English]

Kanban control systems used to optimize inventory levels just in time (JIT) production systems. Evaluation of kanban systems are based on flow control principles and it plays a very important role in production systems. This article presents a new dynamic card control methodology in order to keep a high level of performance measures. The main advantage of the proposed method is easy to adjust parameters. A simulation model for generalized kanban control system with dynamic adjustment of kanban size is proposed. Simulation experiments designed to test the effect of kanban sizes on performance measures such as total production time and amount of work in process, as well. The results of the simulation model indicate the improvement in production rate and reduction of backlog demand by automatic and dynamic adjustment of kanban size. 

کلیدواژه‌ها [English]

  • Generalized kanban control system
  • Pull system
  • Dynamic kanban
  • Simulation

[1] P.L. González-r, J.M. Framinan, and H. Pierreval, "Token-based pull production control systems: an introductory overview", Journal of Intelligent Manufacturing, Vol. 23, No. 1, 2012, pp. 5-22.
[2] N. Selvaraj, "Determining the Number of Kanbans in EKCS: A Simulation Modeling Approach", in Proceedings of the International MultiConference of Engineers and Computer Scientists, 2009.
[3] G. Liberopoulos, and Y. Dallery, "A unified framework for pull control mechanisms in multi-stage manufacturing systems", Annals of Operations Research, Vol. 93, No. 1-4, 2000, pp. 325-355.
[4] Y. Monden, "Smoothed Production Helps Toyota Adapt to Demand Changes and Reduce Inventory", in Toyota Production System, Springer, 1994, pp. 63-73.
[5] T. Ōno, "Toyota production system: beyond large-scale production", Productivity press, 1988.
[6] Y. Sugimori, et al., "Toyota production system and kanban system materialization of just-in-time and respect-for-human system", The International Journal of Production Research, Vol. 15, No. 6, 1977, pp. 553-564.
[7] M. Lage Junior, and M. Godinho Filho, "Variations of the kanban system: literature review and classification", International Journal of Production Economics, Vol. 125, No. 1, 2010, pp. 13-21.
[8] S.C. Aggarwal, and S. Aggarwal, "The management of manufacturing operations: an appraisal of recent developments", International Journal of Operations & Production Management, Vol. 5, No. 3, 1985, pp. 21-38.
[9] H. Grünwald, P. Striekwold, and P. Weeda, "A framework for quantitative comparison of production control concepts", THE INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, Vol. 27, No. 2, 1989, pp. 281-292.
[10] L.P. Rees, et al., "Dynamically adjusting the number of kanbans in a just-in-time production system using estimated values of leadtime", IIE transactions, Vol. 19, No. 2, 1987, pp. 199-207.
[11] S.M. Gupta, and Y.A. Al-Turki, "An algorithm to dynamically adjust the number of kanbans in stochastic processing times and variable demand environment", Production Planning & Control, Vol. 8, No. 2, 1997, pp. 133-141.
[12] J.F. BARD, and B. GOLANY, "Determining the number of kanbans in a multiproduct, multistage production system", THE INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, Vol. 29, No. 5, 1991, pp. 881-895.
[13] K. Ohno, "The optimal control of just-in-time-based production and distribution systems and performance comparisons with optimized pull systems", European Journal of Operational Research, Vol. 213, No. 1, 2011, pp. 124-133.
[14] N. Selvaraj, "Determining the number of Kanbans in EKCS: a simulation modeling approach", in Proceedings of the International Multi-Conference of Engineers and Computer Scientists IMECS, 2009.
[15] S. Gstettner, and H. KUHN‡, "Analysis of production control systems kanban and CONWIP", International journal of production research, Vol. 34, No. 11, 1996, pp. 3253-3273.
[16] M.D. Mascolo, Y. Frein, and Y. Dallery, "An analytical method for performance evaluation of kanban controlled production systems", Operations Research, Vol. 44, No. 1, 1996, pp. 50-64.
[17] O. Wormgoor, "Performance evaluation of generalized kanban systems", Dissertation, Faculty of Mechanical Engineering, University of Twente, Twente, Netherlands, 2001.
[18] C. Alabas, F. Altiparmak, and B. Dengiz, "The optimization of number of kanbans with genetic algorithms", simulated annealing and tabu search. in Evolutionary Computation, Proceedings of the 2000 Congress on, IEEE, 2000.
[19] H. Aytug, C.A. Dogan, and G. Bezmez, "Determining the number of kanbans: a simulation metamodeling approach", Simulation, Vol. 67, No. 1, 1996, pp. 23-32.
[20] K. Ohno, K. Nakashima, and M. Kojima, "Optimal numbers of two kinds of kanbans in a JIT production system", The International Journal of Production Research, Vol. 33, No. 5, 1995, pp. 1387-1401.
[21] M. Özbayrak, G. Cagil, and C. Kubat, "How successfully does JIT handle machine breakdowns in an automated manufacturing system?", Journal of Manufacturing Technology Management, Vol. 15, No. 6, 2004, pp. 479-494.
[22] J.A. Buzacott, and J.G. Shanthikumar, "Design of manufacturing systems using queueing models", Queueing Systems, Vol. 12, No. 1-2, 1992, pp. 135-213.
[23] C. Duri, Y. Frein, and M. Di Mascolo, "Comparison among three pull control policies: kanban, base stock, and generalized kanban", Annals of Operations Research, Vol. 93, No. 1-4, 2000, pp. 41-69.
[24] S. Kotani, T. Ito, and K. Ohno, "Sequencing problem for a mixed-model assembly line in the Toyota production system", International Journal of Production Research, Vol. 42, No. 23, 2004, pp. 4955-4974.

[25] E. Gaury, H. Pierreval, and J.P. Kleijnen, "An evolutionary approach to select a pull system among Kanban, Conwip and Hybrid", Journal of Intelligent Manufacturing, Vol. 11, No. 2, 2000, pp. 157-167.
[26] L.L.P. Marand, et al., "An Adaptive Kanban and Production Capacity Control Mechanism", Advances in Production Management Systems, Competitive Manufacturing for Innovative Products and Services, Springer, 2013, pp. 452-459.
[27] P. Renna, L. Magrino, and R. Zaffina, "Dynamic card control strategy in pull manufacturing systems", International Journal of Computer Integrated Manufacturing, Vol. 26, No. 9, 2013, pp. 881-894.
[28] M. Ettl, and M. Schwehm, "A design methodology for Kanban-controlled production lines using queuing networks and genetic algorithms", Interne Bericht IMMD, Vol. 7, 1994, pp. 15-94.
[29] S. Chaharsooghi, and A. Sajedinejad, "Determination of the number of kanbans and batch sizes in a JIT supply chain system", Sci Iran, Vol. 17, No. 2, 2010, pp. 143-149.
[30] Y. Dallery, and G. Liberopoulos, "Extended kanban control system: combining kanban and base stock", Iie Transactions, Vol. 32, No. 4, 2000, pp. 369-386.
[31] C. Alabas, F. Altiparmak, and B. Dengiz, "A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans", Journal of the Operational Research Society, Vol. 53, No. 8, 2002, pp. 907-914.
[32] P. Shahabudeen, K. Krishnaiah, and M.T. Narayanan, "Design of a two-card dynamic kanban system using a simulated annealing algorithm", The International Journal of Advanced Manufacturing Technology, Vol. 21, No. 10-11, 2003, pp. 754-759.
[33] D.E. Koulouriotis, A.S. Xanthopoulos, and V.D. Tourassis, "Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms", International Journal of Production Research, Vol. 48, No. 10, 2010, pp. 2887-2912.
[34] L.S. Belisário, and H. Pierreval, "Using genetic programming and simulation to learn how to dynamically adapt the number of cards in reactive pull systems", Expert Systems with Applications, Vol. 42, No. 6, 2015, pp. 3129-3141.
[35] P. Renna, "A fuzzy control system to adjust the number of cards in a CONWIP–based manufacturing system", International Journal of Services and Operations Management, Vol. 20, No. 2, 2015, pp. 188-206.
[36] G. Pedrielli, A. Alfieri, and A. Matta, "Integrated simulation–optimisation of pull control systems", International Journal of Production Research, Vol. 53, No. 14, 2015, pp. 4317-4336.
[37] F. Lolli, et al., "A simulative approach for evaluating alternative feeding scenarios in a kanban system", International Journal of Production Research, Vol. 54, No. 14, 2016, pp. 4228-4239.
[38] E. Pierreval, et al. "A simulation optimization approach for reactive ConWIP systems", in Modelling and Simulation (EUROSIM), 2013 8th EUROSIM Congress on, IEEE, 2013.
[39] K. Takahashi, "Comparing reactive Kanban systems", International Journal of Production Research, Vol. 41, No. 18, 2003, pp. 4317-4337.
[40] G. Liberopoulos, et al., "Stochastic Modeling of Manufacturing Systems", Springer, 2006.
[41] R.J. GRAVES, J.M. KONOPKA, and R.J. MILNE, "Literature review of material flow control mechanisms", Production Planning & Control, Vol. 6, No. 5, 1995, pp. 395-403.
[42] L.P. Rees, P.Y. Huang, and B.W. Taylor III, "A comparative analysis of an MRP lot-for-lot system and a Kanban system for a multistage production operation", International journal of production research, Vol. 27, No. 8, 1989, pp. 1427-1443.
[43] J.A. Buzacott, "Queueing models of kanban and MRP controlled production systems", Engineering costs and production economics, Vol. 17, No. 1, 1989, pp. 3-20.
[44] P. Zipkin, "A kanban-like production control system: analysis of simple models", Preprint, 1989.