Abstract
A mathematical model is developed to formulate a cellular manufacturing system with uncertain parameters. In this work, the processing times and demands are stochastic and estimated via expected value and standard deviation after sampling process. The objectives of the proposed mathematical model are to configure machines’ layout in cells so that the inter-cell and intra-cell movements are minimized, the bottlenecks are breakthrough and the profit is increased. Finally, the profit is maximized due to decreasing production cost. The applicability of the proposed mathematical program is illustrated using numerical examples. With respect to the large amount of computational efforts in larger sized problem, a heuristic methodology is developed as solution approach. The properties of the proposed heuristic method are the novel search algorithm and the allocation methodology.
References
1. ChattopadhyayM, SenguptaS, GhoshT, DanPK, MazumdarS. Neuro-genetic impact on cell formation methods of cellular manufacturing system design: a quantitative review and analysis. Comput Ind Eng2013;64:256–72.10.1016/j.cie.2012.09.016Search in Google Scholar
2. WemmerlovU, HyerN. Cellular manufacturing in the US industry: A survey of users. Int J Prod Res1989;27:1511–30.10.1080/00207548908942637Search in Google Scholar
3. ChenM, CaoD. Coordinating production planning in cellular manufacturing environment using Tabu search. Comput Ind Eng2004;46:571–88.10.1016/j.cie.2004.02.002Search in Google Scholar
4. Majazi DalfardV. New mathematical model for problem of dynamic cell formation based on number and average length of intra and intercellular movements. Appl Math Model2013;37:1884–96.10.1016/j.apm.2012.04.034Search in Google Scholar
5. PaydarMM, Saidi-MehrabadM. A hybrid genetic-variable neighborhood search algorithm for the cell formation problem based on grouping efficacy. Comput Oper Res2013;40:980–90.10.1016/j.cor.2012.10.016Search in Google Scholar
6. GhezavatiVR, Jabal-AmeliMS, MakuiA. A new heuristic method for distribution networks considering service constraint and coverage radius. Expert Syst Appl2009;36:5620–9.10.1016/j.eswa.2008.06.130Search in Google Scholar
7. SnyderLV. Facility location under uncertainty: a review. IIE Trans2006;38:537–54.10.1080/07408170500216480Search in Google Scholar
8. EgilmezG, SüerGA, HuangJ. Stochastic cellular manufacturing system design subject to maximum acceptable risk level. Comput Ind Eng2012;63:842–54.10.1016/j.cie.2012.05.006Search in Google Scholar
9. SelimHM, AskinRG, VakhariaAJ. Cell formation in group technology: review, evaluation and direction for future research. Comput Ind Eng1998;34:3–20.10.1016/S0360-8352(97)00147-2Search in Google Scholar
10. MansouriSA, Moattar-HusseinSM, NewmanST. A review of the modern approaches to multi-criteria cell design. Int J Prod Res2000;38:1201–18.10.1080/002075400189095Search in Google Scholar
11. SinghN. Design of cellular manufacturing systems: an invited review. Eur J Oper Res1993;69:281–511.10.1016/0377-2217(93)90016-GSearch in Google Scholar
12. NsakandaAL, DiabyM, PriceWL. Hybrid genetic approach for solving large-scale capacitated cell formation problems with multiple routings. Eur J Oper Res2006;171:1051–70.10.1016/j.ejor.2005.01.017Search in Google Scholar
13. ChenM, CaoD. A robust cell formation approach for varying product demands. Int J Prod Res2005;49:1587–605.10.1080/00207540412331327754Search in Google Scholar
14. SongS, HitomiK. Integrating the production planning and cellular layout for flexible cellular manufacturing. Prod Plan Control1996;7:585–93.10.1080/09537289608930392Search in Google Scholar
15. MungwattanaA. Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility, Ph.D. Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University, Blacksburg, VA, 2000.Search in Google Scholar
16. AnejaYP, KamounH. Scheduling of parts and robot activities in a two machine robotic cell. Comput Oper Res1999;26:297–312.10.1016/S0305-0548(98)00063-XSearch in Google Scholar
17. LogendranR, NudtasomboonN. Minimizing the makespan of a group scheduling problem: a new heuristic. Int J Prod Econ1991;22:217–30.10.1016/0925-5273(91)90098-ESearch in Google Scholar
18. SolimanpurM, PremV, RaviS. A heuristic to minimize makespan of cell scheduling problem. Int J Prod Econ2004;88:231–41.10.1016/S0925-5273(03)00196-8Search in Google Scholar
19. TaylorJF, HamI. The use of a microcomputer for grouping scheduling, Proceedings of the ninth North American manufacturing research conference (NAMRC), Society of Manufacturing Engineers, 483–91, 1981.Search in Google Scholar
20. TsaiCC, ChuCH, BartaT. Analysis and modeling of a manufacturing cell formation problem with fuzzy integer programming. IIE Trans1997;29:533–47.10.1080/07408179708966364Search in Google Scholar
21. VakhariaAJ, KakuBK. Redesigning a cellular manufacturing system to handle long-term demand changes: A methodology and investigation. Decis Sci1993;24:909–17.10.1111/j.1540-5915.1993.tb00496.xSearch in Google Scholar
22. WuXD, ChuCH, WangYF, YanWL. Concurrent design of cellular manufacturing systems: a genetic algorithm approach. Int J Prod Res2006;44:1217–41.10.1080/00207540500338252Search in Google Scholar
23. AllisonJD. Combining Petrov heuristic and CDS heuristic in group scheduling problems. Comput Ind Eng1990;19:457–61.10.1016/0360-8352(90)90158-ISearch in Google Scholar
24. VakhariaAJ, ChangYL. A simulated annealing approach to scheduling a manufacturing cell. Naval Res Logistics1990;37:559–77.10.1002/1520-6750(199008)37:4<559::AID-NAV3220370409>3.0.CO;2-8Search in Google Scholar
25. SeifoddiniH. A probabilistic model for machine cell formation. J Manuf Syst1990;9:69–75.10.1016/0278-6125(90)90070-XSearch in Google Scholar
26. RafieiH, GhodsiR. A bi-objective mathematical model toward dynamic cell formation considering labor utilization. Appl Math Model2013;37:2308–16.10.1016/j.apm.2012.05.015Search in Google Scholar
27. TilsleyR, LewisFA. Flexible cell production systems – a realistic approach. Ann CIRP1977;25:269–71.Search in Google Scholar
28. Tavakkoli-MoghaddamR, JavadianN, JavadiB, SafaeiN. Design of a facility layout problem in cellular manufacturing systems with stochastic demands. Appl Math Comput2007;184:721–8.10.1016/j.amc.2006.05.172Search in Google Scholar
©2015 by De Gruyter
