Hachicha, Wafik and Masmoudi, Faouzi and Haddar, Mohamed (2007): An improvement of a cellular manufacturing system design using simulation analysis. Published in: International journal of simulation modeling , Vol. 6, No. 4 (December 2007): pp. 193-205.
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Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical example
|Item Type:||MPRA Paper|
|Original Title:||An improvement of a cellular manufacturing system design using simulation analysis|
|Keywords:||Cell Formation; Exceptional Elements; Simulation; Alternative costs; Improvement|
|Subjects:||C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
|Depositing User:||Wafik HACHICHA|
|Date Deposited:||01. Jun 2008 04:23|
|Last Modified:||12. Feb 2013 11:30|
 Burbidge, J.L. (1992). Change to group technology: Process organization is obsolete, Int. J. of Production Research, Vol. 30, No.5, 1209–1219.
 Shambu, G. (1996). Performance evaluation of cellular manufacturing systems: a taxonomy and review of research, Int. J. of Operations & Production Management, Vol. 8, 81-103.
 Singh, N.; Rajamani, D. (1996). Cellular manufacturing systems: Design, Planning and control. Chapman & Hall, New York.
 King, J.R. (1980). Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm. Int. J. of Production Research, Vol.18, pp. 213–232.
 Chan, H.; Milner, D. (1982). Direct clustering algorithm for group formation in cellular manufacturing, Journal of Manufacturing Systems, Vol. 1, No.1, pp. 65–67.
 Hachicha, W.; Masmoudi, F.; Haddar, M. (2008). Formation of machine groups and part families in cellular manufacturing systems using a correlation analysis approach. Int. J. of Advanced Manufacturing Technology. Vol. 36: N° 11-12. pp. 1157-1169  Gupta, T.; Saifoddini, H. (1990). Production data based similarity coefficient for machine-component grouping decisions in the design of a cellular manufacturing system, Int. J. of Production Research, Vol. 28, 1247-1269.
 Slim, H.; Askin, R.; Vakharia, A. J. (1998). Cell formation in Group technology: review, evaluation and directions for future research, Computers & Industrial engineering, Vol 34, 3-20
 Hachicha, W.; Masmoudi, F.; Haddar, M. (2006). A correlation analysis approach of cell formation in cellular manufacturing system with incorporated production data. Int. J. of Manufacturing Research, Vol. 1, No. 3, 332–353.
 Sarker, B. R.; Balan, C. V. (1996). Cell formation with operation times of jobs foe even distribution of workloads, Int. J. of Production Research, Vol. 34, No. 5, 1447–1468.
 Shafer, S.; Kern, G.; Wei, JC. (1992). A mathematical programming approach for dealing with exceptional elements in cellular manufacturing, Int. J. of Production Researches, Vol. 30, 1029-1036.
 Wemmerlöv, U.; Hyer, N.L. (1986). The part family/machine group identification problem in cellular manufacturing, Journal of Operation Management, Vol. 6, 125-147.
 McAuley, J., (1972). Machine grouping for efficient production. The production Engineer, Vol. 56, pp. 451-454.
 King, J.R. (1980). Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm, Int. J. of Production Research, Vol. 18, 213–232.
 Burbidge, J.L. (1975). The introduction of Group technology, New York:Halster Press and John Wiley.
 Kusiak, A. (1987). The generalized group technology concept, Int. J. of Production Research, Vol. 25, 561–569.
 Seifoddini, H., (1989). Duplication process in machines cells formation in group technology, IIE Transactions, Vol. 21, No. 4, 382-388.
 Foulds, L.R.; French, A.P.; Wilson, J.M. (2006). The sustainable cell formation problem: manufacturing cell creation with machine modification costs. Computers & Operations Research, Vol. 33, 1010-1032.
 Cheng, C. H.; Goh, C. H.; Lee, A. (2001). Designing group technology manufacturing systems using heuristic branching rules, Computers & Industrial engineering, Vol. 40, 117-131.
 Kamrani, A.; Hubbard, K.; Parsaep, H.; Leew, H.,R. (1998). Simulation-based methodology for machine cell design, Computers & Industrial Engineering, Vol. 34, No. 1, 173-188.
 Habchi, G.; Berchet, C. (2003). A model for manufacturing systems simulation with a control dimension, Simulation Modelling Practice and Theory, Vol. 11, 21–44
 Masmoudi, F. (2006). Sizing manufacturing cell machines based on the simulation and an expert system, Int. J. of Simulation Modelling, Vol. 5, No. 2, 45-55.
 Faizul, H.; Douglas, A.H.; Zubair, M.M.(2001). A simulation analysis of factors influencing the flow time and through-put performances of functional and cellular layouts, Integrated Manufacturing Systems, Vol. 12, 285- 295.
 Burgess, A. G.; Morgan, I.; Vollmann, T. E. (1993). Cellular manufacturing: its impact on the total factory, Int. J. of Production Research, Vol. 31, 2059-2077.
 Shambu, G.; Suresh, N.C. (2000). Performance of hybrid cellular manufacturing systems: A computer simulation investigation, European Journal of Operational Research, Vol. 120, 436-458
 Polajnar, A.; Buchmeister, B.; Leber, M.A. (1995). Analysis of different transport solutions in the flexible manufacturing cell by using computer simulation, Int. J. of Operations and Production Management. Vol. 15, No. 6, 51–58.
 Masmoudi, F.; Masmoudi, Y.; Maalej, Y.A. (2006). Optimization of product transfer with constraint in robotic cell using simulation, Int. J. of Simulation Modelling, Vol. 5, N°3, 89-100.
 Shafer, S.M.; Meredith, J. R. (1993). An empirically-based simulation study of functional versus cellular layouts with operations overlapping, Int. J. of Operations and Production Management, Vol.13, 47-62.
 Law, M.; Kelton, W.D. (2000). Simulation modeling and Analysis, Mc Graw Hill, New York.
 Selen, W.J.; Ashayeri, J. (2001). Manufacturing cell performance improvement: a simulation study, Robotics and Computer Integrated Manufacturing, Vol.17, 169-176.
 Kelton, W.D.; Sadawski, R.P.; Sadawski, D.A. (2002). Simulation with Arena, Mc Graw Hill, New York.
 Arena Standard User’s Guide, Doc ID ARENAS-UM001C-EN-P, (2002), Rochwell Software Inc.
 Shambu, G.; Suresh, N.C. (2000). Performance of hybrid cellular manufacturing systems: A computer simulation investigation, European Journal of Operational Research, Vol. 120, 436-458.