Development of a Web-Based Decision Support System for Cell Formation Problems Considering Alternative Process Routings and Machine Sequences
Author(s)
Chin-Chih Chang
ABSTRACT
In this study, we use the respective advantages of the tabu search (TS) and the Web-based technologies to develop a Web-based decision support system (DSS) for cell formation (CF) problems considering alternative process routings and machine sequences simultaneously. With the assistance of our developed Web-based system, the CF practitioners in the production departments can interact with the systems without knowing the details of algorithms and can get the best machine cells and part families with minimize the total intercellular movement wherever and whenever they may need it. To further verify the feasibility and effectiveness of the system developed, an example taken from the literature is ado- pted for illustrational purpose. Moreover, a set of test problems with various sizes drawn from the literature is used to test the performance of the proposed system. Corresponding results are compared to several well-known algorithms previously published. The results indicate that the proposed system improves the best results found in the literature for 67% of the test problems. These show that the proposed system should thus be useful to both practitioners and researchers.
In this study, we use the respective advantages of the tabu search (TS) and the Web-based technologies to develop a Web-based decision support system (DSS) for cell formation (CF) problems considering alternative process routings and machine sequences simultaneously. With the assistance of our developed Web-based system, the CF practitioners in the production departments can interact with the systems without knowing the details of algorithms and can get the best machine cells and part families with minimize the total intercellular movement wherever and whenever they may need it. To further verify the feasibility and effectiveness of the system developed, an example taken from the literature is ado- pted for illustrational purpose. Moreover, a set of test problems with various sizes drawn from the literature is used to test the performance of the proposed system. Corresponding results are compared to several well-known algorithms previously published. The results indicate that the proposed system improves the best results found in the literature for 67% of the test problems. These show that the proposed system should thus be useful to both practitioners and researchers.
KEYWORDS
Web-Based, Cell Formation, Tabu Search, Decision Support System, Alternative Process Routings
Web-Based, Cell Formation, Tabu Search, Decision Support System, Alternative Process Routings
Cite this paper
nullC. Chang, "Development of a Web-Based Decision Support System for Cell Formation Problems Considering Alternative Process Routings and Machine Sequences," Journal of Software Engineering and Applications, Vol. 3 No. 2, 2010, pp. 160-166. doi: 10.4236/jsea.2010.32020.
nullC. Chang, "Development of a Web-Based Decision Support System for Cell Formation Problems Considering Alternative Process Routings and Machine Sequences," Journal of Software Engineering and Applications, Vol. 3 No. 2, 2010, pp. 160-166. doi: 10.4236/jsea.2010.32020.
References
[1] S. Heragu, “Facilities design,” Massachusetts: PWS Publishing Company, Boston, 1997. [2] U. Wemmerlov and N. Hyer, “Research issues in cellular manufacturing,” International Journal of Production Re-search, Vol. 25, pp. 413–431, 1987. [3] A. Kusiak, “Intelligent manufacturing systems,” New Jersey: Prentice Hall, Englewood Cliffs, 1990. [4] Y. Yin and K. Yasuda, “Similarity coefficient methods applied to the cell formation problem: A taxonomy and review,” International Journal of Production Economics, Vol. 101, pp. 329–352, 2006. [5] A. Kusiak, “The generalized group technology concept,” International Journal of Production Research, Vol. 25, pp. 561–569, 1987. [6] M. S. J. Ameli and J. Arkat, “Cell formation with alterna-tive process routings and machine reliability considera-tion,” International Journal of Advanced Manufacturing Technology, Vol. 35, pp. 761–768, 2008. [7] F. Boctor, “A linear formulation of the machine-part cell formation problem,” International Journal of Production Research, Vol. 29, No. 2, pp. 343–356, 1991. [8] Y. Y. Won and K. C. Lee, “Group technology cell forma-tion considering operation sequences and production vol- umes,” International Journal of Production Research, Vol. 39, No. 13, pp. 2755–2768, 2001. [9] S. Sofianopoulou, “Manufacturing cells design with alter- native process plans and/or replicate machines,” Interna-tional Journal of Production Research, Vol. 37, pp. 707– 720, 1999. [10] M. Boulif and K. Atif, “A new branch-&-bound-enhanced genetic algorithm for the manufacturing cell formation problem,” Computers and Operations Research, Vol. 33, pp. 2219–2245, 2006. [11] T.-H. Wu, S.-H. Chung, and C.-C. Chang, “Hybrid simu-lated annealing algorithm with mutation operator to the cell formation problem with alternative process routings,” Expert Systems with Applications, Vol. 36, pp. 3652– 3661, 2008. [12] G. J. Nair and T. T. Narendran, “CASE: A clustering algorithm for cell formation with sequence data,” Interna-tional Journal of Production Research, Vol. 36, pp. 157– 179, 1998. [13] J. McAuley, “Machine grouping for efficient production,” Production Engineer, Vol. 52, pp. 53–57, 1972. [14] S. Lozano, B. Adenso-Diaz, and L. Onieva, “A one-step Tabu search algorithm for manufacturing cell design,” Journal of the Operational Research Society, Vol. 50, pp. 509–516, 1999. [15] G. Y. Tian, G. Yin, and D. Taylor, “Internet-based manu-facturing: A review and a new infrastructure for distrib-uted intelligent manufacturing,” Journal of Intelligent Manufacturing, Vol. 13, No. 5, pp. 323–338, 2002. [16] J. Lee, “E-manufacturing systems: Fundamental and too- ls,” Robotics and Computer-Integrated Manufacturing, Vol. 9, No. 6, pp. 501–507, 2003. [17] C. S. Smith and P. K. Wright, “CyberCut: A world-wide web-based design-to-fabrication tool,” Journal of Intelli-gent Manufacturing, Vol. 15, No. 6, pp. 432–442, 1996. [18] N. Wu, “A concurrent approach to cell formation and assignment of identical machines in group technology,” International Journal of Production Research, Vol. 36, pp. 2099–2114, 1998. [19] T. Gupta and H. Seifoddini, “Production data based simi-larity coefficient for machine-part grouping decisions in the design of a cellular manufacturing system,” Interna-tional Journal of Production Research, Vol. 28, pp. 1247– 1269, 1990. [20] R. Nagi, G. Harlarakis, and J. M. Proth, “Multiple rout-ings and capacity considerations in group technology ap-plications,” International Journal of Production Research, Vol. 28, pp. 2243–2257, 1990.
[1] S. Heragu, “Facilities design,” Massachusetts: PWS Publishing Company, Boston, 1997. [2] U. Wemmerlov and N. Hyer, “Research issues in cellular manufacturing,” International Journal of Production Re-search, Vol. 25, pp. 413–431, 1987. [3] A. Kusiak, “Intelligent manufacturing systems,” New Jersey: Prentice Hall, Englewood Cliffs, 1990. [4] Y. Yin and K. Yasuda, “Similarity coefficient methods applied to the cell formation problem: A taxonomy and review,” International Journal of Production Economics, Vol. 101, pp. 329–352, 2006. [5] A. Kusiak, “The generalized group technology concept,” International Journal of Production Research, Vol. 25, pp. 561–569, 1987. [6] M. S. J. Ameli and J. Arkat, “Cell formation with alterna-tive process routings and machine reliability considera-tion,” International Journal of Advanced Manufacturing Technology, Vol. 35, pp. 761–768, 2008. [7] F. Boctor, “A linear formulation of the machine-part cell formation problem,” International Journal of Production Research, Vol. 29, No. 2, pp. 343–356, 1991. [8] Y. Y. Won and K. C. Lee, “Group technology cell forma-tion considering operation sequences and production vol- umes,” International Journal of Production Research, Vol. 39, No. 13, pp. 2755–2768, 2001. [9] S. Sofianopoulou, “Manufacturing cells design with alter- native process plans and/or replicate machines,” Interna-tional Journal of Production Research, Vol. 37, pp. 707– 720, 1999. [10] M. Boulif and K. Atif, “A new branch-&-bound-enhanced genetic algorithm for the manufacturing cell formation problem,” Computers and Operations Research, Vol. 33, pp. 2219–2245, 2006. [11] T.-H. Wu, S.-H. Chung, and C.-C. Chang, “Hybrid simu-lated annealing algorithm with mutation operator to the cell formation problem with alternative process routings,” Expert Systems with Applications, Vol. 36, pp. 3652– 3661, 2008. [12] G. J. Nair and T. T. Narendran, “CASE: A clustering algorithm for cell formation with sequence data,” Interna-tional Journal of Production Research, Vol. 36, pp. 157– 179, 1998. [13] J. McAuley, “Machine grouping for efficient production,” Production Engineer, Vol. 52, pp. 53–57, 1972. [14] S. Lozano, B. Adenso-Diaz, and L. Onieva, “A one-step Tabu search algorithm for manufacturing cell design,” Journal of the Operational Research Society, Vol. 50, pp. 509–516, 1999. [15] G. Y. Tian, G. Yin, and D. Taylor, “Internet-based manu-facturing: A review and a new infrastructure for distrib-uted intelligent manufacturing,” Journal of Intelligent Manufacturing, Vol. 13, No. 5, pp. 323–338, 2002. [16] J. Lee, “E-manufacturing systems: Fundamental and too- ls,” Robotics and Computer-Integrated Manufacturing, Vol. 9, No. 6, pp. 501–507, 2003. [17] C. S. Smith and P. K. Wright, “CyberCut: A world-wide web-based design-to-fabrication tool,” Journal of Intelli-gent Manufacturing, Vol. 15, No. 6, pp. 432–442, 1996. [18] N. Wu, “A concurrent approach to cell formation and assignment of identical machines in group technology,” International Journal of Production Research, Vol. 36, pp. 2099–2114, 1998. [19] T. Gupta and H. Seifoddini, “Production data based simi-larity coefficient for machine-part grouping decisions in the design of a cellular manufacturing system,” Interna-tional Journal of Production Research, Vol. 28, pp. 1247– 1269, 1990. [20] R. Nagi, G. Harlarakis, and J. M. Proth, “Multiple rout-ings and capacity considerations in group technology ap-plications,” International Journal of Production Research, Vol. 28, pp. 2243–2257, 1990.