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Designing a mathematical model for dynamic cellular manufacturing systems considering production planning and worker assignment. (English) Zbl 1201.90120
Summary: Since workers have an important role in doing jobs on machines, assignment of workers to cells becomes a crucial factor for full utilization of cellular manufacturing systems. This paper presents an integer mathematical programming model for the design of cellular manufacturing systems in a dynamic environment. The advantages of the proposed model are as follows: considering multi-period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, available time of workers, and worker assignment. The aim of the proposed model is to minimize holding and backorder costs, inter-cell material handling cost, machine and reconfiguration costs and hiring, firing and salary costs. Computational results are presented by solving some examples.
MSC:
90B80Discrete location and assignment
References:
[1]Wemmerlov, U.; Hyer, N. L.: Procedures for the part-family/machine group identification problem in cellular manufacturing, Journal of operations management 6, No. 2, 125-147 (1986)
[2]Kusiak, A.; Chow, W. S.: Efficient solving of the group technology problem, Journal of manufacturing systems 6, No. 2, 117-124 (1987)
[3]Reisman, A.; Kumar, A.; Motwani, J.; Cheng, C. H.: Cellular manufacturing: a statistical review of the literature (1965–1995), Operations research 45, No. 4, 508-520 (1997) · Zbl 0889.90081 · doi:10.1287/opre.45.4.508
[4]Selim, H. M.; Askin, R. G.; Vakharia, A. J.: Cell formation in group technology: review, evaluation and directions for future research, Computers industrial engineering 34, 3-20 (1998)
[5]Singh, N.: Design of cellular manufacturing systems: an invited review, European journal of operational research 69, No. 3, 281-511 (1993)
[6]Mansouri, S. A.; Husseini, S. M. Moattar; Newman, S. T.: A review of the modern approach to multi-criteria cell design, International journal of production research 38, 1201-1218 (2000) · Zbl 0945.90529 · doi:10.1080/002075400189095
[7]Yin, Y.; Yasuda, K.: Similarity coefficient methods applied to the cell formation problem: a taxonomy and review, International journal of production economics 101, 329-352 (2006)
[8]Balakrishnan, J.; Cheng, C. H.: Multi-period planning and uncertainty issues in cellular manufacturing: a review and future directions, European journal of operational research 177, 281-309 (2007) · Zbl 1102.90317 · doi:10.1016/j.ejor.2005.08.027
[9]Rheault, M.; Drolet, J.; Abdulnour, G.: Physically reconfigurable virtual cells: a dynamic model for a highly dynamic environment, Computers industrial engineering 29, No. 1–4, 221-225 (1995)
[10]Chen, M.: A mathematical programming model for systems reconfiguration in a dynamic cell formation condition, Annals of operations research 77, No. 1, 109-128 (1998) · Zbl 0897.90106 · doi:10.1023/A:1018917109580
[11]Wicks, E. M.; Reasor, R. J.: Designing cellular manufacturing systems with dynamic part populations, IIE transactions 31, 11-20 (1999)
[12]A. Mungwattana, Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility, Ph.D. Thesis, Virginia Polytechnic Institute and State University, Blackburg, VA, 2000.
[13]Balakrishnan, J.; Cheng, C. H.: Dynamic cellular manufacturing under multi-period planning horizons, Journal of manufacturing technology management 16, No. 5, 516-530 (2005)
[14]Defersha, F.; Chen, M.: A comprehensive mathematical model for the design of cellular manufacturing systems, International journal of production economics 103, 767-783 (2006)
[15]Safaei, N.; Saidi-Mehrabad, M.; Jabal-Ameli, M. S.: A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system, European journal of operational research 185, 563-592 (2008) · Zbl 1137.90471 · doi:10.1016/j.ejor.2006.12.058
[16]Defersha, F. M.; Chen, M.: A linear programming embedded genetic algorithm for an integrated cell formation and lot sizing considering product quality, European journal of operational research 187, No. 1, 46-69 (2008) · Zbl 1149.90049 · doi:10.1016/j.ejor.2007.02.040
[17]Ahkioon, S.; Bulgak, A. A.; Bektas, T.: Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration, European journal of operational research 192, 414-428 (2009) · Zbl 1157.90391 · doi:10.1016/j.ejor.2007.09.023
[18]Safaei, N.; Tavakkoli-Moghaddam, R.: Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing, International journal of production economics 120, No. 2, 301-314 (2009)
[19]Nembhard, D. A.: Heuristic approach for assigning workers to task based on individual learning rates, International journal of production research 39, No. 8, 1968-1995 (2001)
[20]Norman, B. A.; Tharmmaphornphilas, W.; Needy, K. L.; Bidanda, B.; Warner, R. C.: Worker assignment in cellular manufacturing considering technical and human skills, International journal of production research 40, No. 6, 1479-1492 (2002) · Zbl 1063.90521 · doi:10.1080/00207540110118082
[21]Bidanda, B.; Ariyawongrat, P.; Needy, K. M.; Norman, B. A.; Tharmmaphornphilas, W.: Human-related issues in manufacturing cell design, implementation, and operation: a review and survey, Computer industrial engineering 48, 507-523 (2005)
[22]Wirojanagud, P.; Gel, E. S.; Fowler, J. W.; Cardy, R. L.: Modeling inherent worker difference for workforce planning, International journal of production research 45, No. 3, 525-553 (2007)
[23]Aryanezhad, M. B.; Deljoo, V.; Al-E-Hashem, S. M. J. Mirzapour: Dynamic cell formation and the worker assignment problem: a new model, International journal of advanced manufacturing technology 38, No. 3–4 (2008)
[24]M. Solimanpur, I. Mahdavi, A. Aalaei, M.M. Paydar, Multi-objective cell formation and production planning in dynamic virtual cellular manufacturing systems, in: International Conference on Business and Information, BAI 2009, Kuala Lumpur, Malaysia, July 6–8, 2009.
[25]A. Ballakur, An investigation of part family/machine group formation in designing a cellular manufacturing system, Ph.D. Thesis, University of Wisconsin, Madison, WI, 1985.
[26]King, J.; Nakornchai, V.: Machine-component group formation in group technology: review and extension, International journal of production research 20, No. 2, 117-133 (1982)
[27]Logendran, R.; Ramakrishna, P.; Sriskandarajah, C.: Tabu search-based heuristics for cellular manufacturing systems in the presence of alternative process plans, International journal of production research 32, 273-297 (1994) · Zbl 0911.90187 · doi:10.1080/00207549408956933