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Machine-part cell formation using biclustering

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  • Boutsinas, Basilis

Abstract

Cellular manufacturing is the cornerstone of many modern flexible manufacturing techniques, taking advantage of the similarities between parts in order to decrease the complexity of the design and manufacturing life cycle. Part-Machine Grouping (PMG) problem is the key step in cellular manufacturing aiming at grouping parts with similar processing requirements or similar design features into part families and by grouping machines into cells associated to these families. The PMG problem is NP-complete and the different proposed techniques for solving it are based on heuristics. In this paper, a new approach for solving the PMG problem is proposed which is based on biclustering. Biclustering is a methodology where rows and columns of an input data matrix are clustered simultaneously. A bicluster is defined as a submatrix spanned by both a subset of rows and a subset of columns. Although biclustering has been almost exclusively applied to DNA microarray analysis, we present that biclustering can be successfully applied to the PMG problem. We also present empirical results to demonstrate the efficiency and accuracy of the proposed technique with respect to related ones for various formations of the problem.

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  • Boutsinas, Basilis, 2013. "Machine-part cell formation using biclustering," European Journal of Operational Research, Elsevier, vol. 230(3), pages 563-572.
    • Handle: RePEc:eee:ejores:v:230:y:2013:i:3:p:563-572
    DOI: 10.1016/j.ejor.2013.05.007
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    1. Stanfel, Larry E., 1985. "Machine clustering for economic production," Engineering Costs and Production Economics, Elsevier, vol. 9(1-3), pages 73-81, April.
    2. Sarker, Bhaba R., 2001. "Measures of grouping efficiency in cellular manufacturing systems," European Journal of Operational Research, Elsevier, vol. 130(3), pages 588-611, May.
    3. Nsakanda, Aaron Luntala & Diaby, Moustapha & Price, Wilson L., 2006. "Hybrid genetic approach for solving large-scale capacitated cell formation problems with multiple routings," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1051-1070, June.
    4. Balachandran Vaidyanathan & Ravindra K. Ahuja, 2010. "Fast Algorithms for Specially Structured Minimum Cost Flow Problems with Applications," Operations Research, INFORMS, vol. 58(6), pages 1681-1696, December.
    5. Wu, Tai-Hsi & Chung, Shu-Hsing & Chang, Chin-Chih, 2010. "A water flow-like algorithm for manufacturing cell formation problems," European Journal of Operational Research, Elsevier, vol. 205(2), pages 346-360, September.
    6. Lee, Shine-Der & Chiang, Chih-Ping, 2002. "Cell formations in the uni-directional loop material handling environment," European Journal of Operational Research, Elsevier, vol. 137(2), pages 401-420, March.
    7. Kaparthi, Shashidhar & Suresh, Nallan C. & Cerveny, Robert P., 1993. "An improved neural network leader algorithm for part-machine grouping in group technology," European Journal of Operational Research, Elsevier, vol. 69(3), pages 342-356, September.
    8. Papaioannou, Grammatoula & Wilson, John M., 2010. "The evolution of cell formation problem methodologies based on recent studies (1997-2008): Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 206(3), pages 509-521, November.
    9. Ravi Kumar, K. & Kusiak, Andrew & Vannelli, Anthony, 1986. "Grouping of parts and components in flexible manufacturing systems," European Journal of Operational Research, Elsevier, vol. 24(3), pages 387-397, March.
    10. Yang, Miin-Shen & Yang, Jenn-Hwai, 2008. "Machine-part cell formation in group technology using a modified ART1 method," European Journal of Operational Research, Elsevier, vol. 188(1), pages 140-152, July.
    11. S Lozano & B Adenso-Díaz & I Eguia & L Onieva, 1999. "A one-step tabu search algorithm for manufacturing cell design," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(5), pages 509-516, May.
    12. Defersha, Fantahun M. & Chen, Mingyuan, 2008. "A linear programming embedded genetic algorithm for an integrated cell formation and lot sizing considering product quality," European Journal of Operational Research, Elsevier, vol. 187(1), pages 46-69, May.
    13. Xambre, Ana R. & Vilarinho, Pedro M., 2003. "A simulated annealing approach for manufacturing cell formation with multiple identical machines," European Journal of Operational Research, Elsevier, vol. 151(2), pages 434-446, December.
    14. Basilis Boutsinas, 2002. "Accessing Data Mining Rules Through Expert Systems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 1(04), pages 657-672.
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