{"title":"Performance Analysis of a Flexible Manufacturing Line Operated Under Surplus-based Production Control","authors":"K. K. Starkov, A. Y. Pogromsky, I. J. B. F. Adan, J. E. Rooda","volume":59,"journal":"International Journal of Industrial and Manufacturing Engineering","pagesStart":2245,"pagesEnd":2252,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/13073","abstract":"
In this paper we present our results on the performance analysis of a multi-product manufacturing line. We study the influence of external perturbations, intermediate buffer content and the number of manufacturing stages on the production tracking error of each machine in the multi-product line operated under a surplusbased production control policy. Starting by the analysis of a single machine with multiple production stages (one for each product type), we provide bounds on the production error of each stage. Then, we extend our analysis to a line of multi-stage machines, where similarly, bounds on each production tracking error for each product type, as well as buffer content are obtained. Details on performance of the closed-loop flow line model are illustrated in numerical simulations.<\/p>\r\n","references":"[1] J. R. Montoya-Torres, \"A literature survey on the design approaches and\r\noperational issues of automated wafer-transport systems for wafer fabs,\"\r\nProduction Planning and Control, vol. 17, no. 7, pp. 648-663, 2006.\r\n[2] J. Li, D. Blumenfeld, N. Huang, and J. Alden, \"Throughput analysis\r\nof production systems: recent advances and future topics,\" International\r\nJournal of Production Research, vol. 47, pp. 3823-3851, 2009, 4.\r\n[3] S. Gershwin, \"Design and operation of manufacturing systems: the\r\ncontrol-point policy,\" IIE Transactions, vol. 32, pp. 891-906, 2000.\r\n[4] M. Ortega and L. Lin, \"Control theory applications to the productioninventory\r\nproblem:a review,\" International Journal of Production\r\nResearch, vol. 42, no. 11, pp. 2303-2322, 2004.\r\n[5] H. Sarimveis, P. Patrinos, C. Tarantilis, and C. Kiranoudis, \"Dynamic\r\nmodeling and control of supply chain systems: A review,\" Computers\r\nand Operations Research, vol. 35, pp. 3530-3561, 2008.\r\n[6] A. Bonvik, C. Couch, and S. Gershwin, \"A comparison of productionline\r\ncontrol mechanisms,\" International Journal of Production Research,\r\nvol. 35, no. 3, pp. 789-804, 1997.\r\n[7] H. K. Khalil, Nonlinear Systems, 3rd ed. Prentice-Hall, 2002.\r\n[8] S. Dashkovskiy, M. G\u252c\u00bforges, M. Kosmykov, A. Mironchenko, and\r\nL. Naujok, \"Modeling and stability analysis of autonomously controlled\r\nproduction networks,\" Logistic Research, vol. 3, pp. 145-157, 2011.\r\n[9] J. Perkins, C. Humes, and P. Kumar, \"Distributed scheduling of flexible\r\nmanufacturing systems: Stability and performance,\" IEEE Transactions\r\non Robotics and Automation, vol. 10, pp. 133-141, 1994.\r\n[10] J. Somlo, \"Suitable switching policies for fms scheduing,\" Mechatronics,\r\nvol. 14, pp. 199-225, 2004.\r\n[11] S. Lu and P. Kumar, \"Distributed scheduling based on due dates and\r\nbuffer priorities,\" IEEE Transactions on Automatic Control, vol. 36, pp.\r\n1406-1416, 1991.\r\n[12] R. Quintana, \"Recursive linear control of order release to manufacturing\r\ncells with random yield,\" IIE Transactions, vol. 34, pp. 489-500, 2002.\r\n[13] V. Subramaniam, Y. Rongling, C. Ruifeng, and S. Singh, \"A wip control\r\npolicy for tandem lines,\" International Journal of Production Research,\r\nvol. 47, no. 4, pp. 1127-1149, 2009.\r\n[14] A. Savkin and J. Somlo, \"Optimal distributed real-time scheduling of\r\nflexible manufacturing networks modeled as hybrid dynamical systems,\"\r\nRobotics and Computer-Integrated Manufacturing, vol. 25, pp. 597 -\r\n609, 2009.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 59, 2011"}