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Journal of Intelligent Manufacturing

, Volume 18, Issue 3, pp 383–399 | Cite as

Designing cellular manufacturing systems under dynamic and uncertain conditions

  • Nima Safaei
  • Mohammad Saidi-Mehrabad
  • Masoud Babakhani
Article

Abstract

The paper proposes a fuzzy programming based approach to design a cellular manufacturing system under dynamic and uncertain conditions. The dynamic condition indicates a multi-period planning horizon, in which the product mix and demand in each period can be different. As a result, the best cells designed for one period may not be efficient cells for subsequent periods and some of reconfigurations are required. Uncertain condition implicates to the imprecise nature of the part demand and also the availability of the manufacturing facilities in each period planning. An extended mixed-integer programming model of dynamic cellular manufacturing system, in which some of the coefficients in objective function and constraints are fuzzy quantities, is solved by a developed fuzzy programming based approach. The objective is to determine the optimal cell configuration in each period with maximum satisfaction degree of the fuzzy objective and constraint. To illustrate the behavior of the proposed model and verify the performance of the developed approach, a number of numerical examples are solved and the associated computational results are reported.

Keywords

Dynamic cellular manufacturing systems Uncertain environment Fuzzy Linear programming 

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References

  1. Arikan F., Gungor Z. (2005). A parametric model for cell formation and exceptional elements’ problems with fuzzy parameters. Journal of Intelligent Manufacturing, 16, 103–114CrossRefGoogle Scholar
  2. Askin R.G., Selim H.M., Vakharia A.J. (1997). A methodology for designing flexible cellular manufacturing systems. IIE Transactions, 29, 599–610Google Scholar
  3. Balakrishnan J., Cheng C.H. (2005). Dynamic cellular manufacturing under multi-period planning Horizons. Journal of Manufacturing Technology Management, 16(5): 516–530CrossRefGoogle Scholar
  4. Bellman R.E., Zadeh L.A. (1970). Decision-making in a fuzzy environment. Management Science, 17, 141–164CrossRefGoogle Scholar
  5. Chen M. (1998). A mathematical programming model for systems reconfiguration in a dynamic cell formation condition. Annals of Operations Research, 77, 109–128CrossRefGoogle Scholar
  6. Drolet J., Abdulnour G., Rheault M. (1996). The cellular manufacturing evolution. Computers and Industrial Engineering, 31(1): 139–142CrossRefGoogle Scholar
  7. Gasimov R.N., Yenilmez k. (2002). Solving fuzzy linear programming problems with linear membership functions. Turkish Journal of Mathematics, 26, 375–396Google Scholar
  8. Harhalakis G., Nagi R., Proth J. (1990). An effective heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research, 28, 185–198CrossRefGoogle Scholar
  9. Herrera F., Verdegay J.L., Zimmermann H.J. (1993). Boolean programming problems with fuzzy constraints. Fuzzy Sets and Systems, 55(3): 285–293CrossRefGoogle Scholar
  10. Jeon G., Leep H.R. (2006). Forming part families by using genetic algorithm and designing machine cells under demand changes. Computers & Operations Research, 33, 263–283CrossRefGoogle Scholar
  11. Kannan V., Ghosh S. (1995). Using dynamic cellular manufacturing to simplify scheduling in cell based production systems. Omega, 23(4): 443–452CrossRefGoogle Scholar
  12. Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzy logic-theory and applications (p. 574). Prentice-Hall Inc.Google Scholar
  13. Lai Y.-J., Hwang C.-L. (1992). Fuzzy mathematical programming: Methods and applications. Heidelberg, Springer-VerlagGoogle Scholar
  14. Marcoux Y., Drolet J., Abdulnour G. (1997). Studying the performance Of a dynamic cellular manufacturing system. Computers and Industrial Engineering, 33(1): 239–242CrossRefGoogle Scholar
  15. Rheault M., Drolet J., Abdulnour G. (1995). Physically reconfigurable virtual cells: A dynamic model for a highly dynamic environment. Computers and Industrial Engineering, 29(1–4): 221–225CrossRefGoogle Scholar
  16. Saidi-Mehrabad, M., & Safaei, N. (2006). A new model of dynamic cell formation by a neural approach. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-006-0518-2, Article in press.Google Scholar
  17. Shanker R., Vrat P. (1999). Some design issues in cellular manufacturing using the fuzzy programming approach. International Journal of Production Research, 37(11): 2545–2563CrossRefGoogle Scholar
  18. Song S., Hitomi K. (1996). Integrating the production planning and cellular layout for flexible cellular manufacturing. International Journal of Production. Planning and Control, 7, 585–593CrossRefGoogle Scholar
  19. Tavakkoli-Moghaddam R., Aryanezhad M.B., Safaei N., Azaron A. (2005). Solving a dynamic cell formation problem using metaheuristics. Applied Mathematics and Computation, 170(2): 761–780CrossRefGoogle Scholar
  20. Tsai C.C., Chu C.H., Barta T.A. (1997). Modeling and analysis of a manufacturing cell formation problem with fuzzy mixed integer programming. IIE Transactions, 29, 533–547Google Scholar
  21. Vakharia A.J., Kaku B.K. (1993). Redesigning a cellular manufacturing system to handle long-term demand changes: A methodology and investigation. Decision Sciences, 24(5): 909–929CrossRefGoogle Scholar
  22. Wicks E.M., Reasor R.J. (1999). Designing cellular manufacturing systems with dynamic part populations. IIE Transactions, 31, 11–20Google Scholar
  23. Wilhelm W., Chou C., Chang D. (1998). Integrating design and planning considerations in cell formation. Annals of Operations Research, 77, 97–107CrossRefGoogle Scholar
  24. Zimmermann H.J. (1978). Fuzzy programming and linear programming with several Objective functions. Fuzzy Sets and Systems, 1, 45–55CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Nima Safaei
    • 1
  • Mohammad Saidi-Mehrabad
    • 1
  • Masoud Babakhani
    • 1
  1. 1.Department of Industrial EngineeringIran University of Science and TechnologyTehranIran

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