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Dynamic Cellular Manufacturing System Design for Automated Factories

P. Narendra Mohan, Ch. Srinivasa Rao

Abstract


In this paper, an integrated mathematical model of the multi-period cell formation in a dynamic cellular manufacturing system (DCMS) is proposed with the aim of getting the optimal cost for it. In DCMS, the formed cells in the current period may not be optimal for the next period, so the reconfiguration of the cell is needed, thus we have a tendency to use DCMS. The paper examines the influence of the trade-off between assorted manufacturing costs on the reconfiguration of the cells in Cellular Manufacturing System (CMS) under a lively environment and the proposed model is implemented to a wide range of numerical examples.

Keywords


Dynamic cellular manufacturing system, reconfiguration, alternative routing, production planning

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References


Wemmerlov U, Johnson DJ. Cellular manufacturing at 46 user plants: Implementation experiences and performance improvements. International Journal of Production Research. 1997; 35: 29–49p.

Rheault M, Drolet J, Abdulnour G. Physically reconfigurable virtual cells: A dynamic model for a highly dynamic environment. Computers and Industrial Engineering. 1995; 29(1–4): 221–5p.

Kim B, Kim S. Extended model for a hybrid production planning approach. International Journal of Production Economics. 2001; 73: 165–73p.

Wicks E-M, Reasor R-J. Designing cellular manufacturing systems with dynamic part populations. IIE Transactions. 1999; 31: 11–20p.

Defersha F-M, Chen M. Machine cell formation using a mathematical model and a genetic algorithm based heuristic. International Journal of Production Research. 2006a; 44(12): 2421–44p.

Safaei N, Tavakkoli-Moghaddam R, Jabal- Ameli S. A generalized cell formation problem in dynamic environment with different inter and intra-cell batch sizes. In: Dolgui A, Pereira C, Morel G (Eds). Information Control Problems in Manufacturing. Proceedings of the 12th IFAC International Symposium. Elsevier Science, Saint-Etienne, France. 17–19 May 2006; 2: 383–8p.

Safaei N, Saidi-Mehrabad M, Jabal-Ameli MS. A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. European Journal of Operational Research. 2008; 185: 563–92p.

Sankaran S, Kasilingam RG. On cell size and machine requirements planning in group technology systems. European Journal of Operational Research. 1993;

DCMS Design for Automated Factories Mohan and Rao

JoPRM (2014) 12-30 © STM Journals 2014. All Rights Reserved Page 29

: 373–83p.

Safaei N, Tavakkoli-Moghaddam R. Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems. Int. J. Production Economics. 2009; 120: 301–14p.

Harhalakis G, Nagi R, Proth J. An efficient heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research. 1990; 28(1): 185–98p.

Vakharia A, Kaku B. Redesigning a cellular manufacturing system to handle long-term demand changes: A methodology and investigation. Decision Sciences. 1993; 24 (5): 84–97p.

Balakrishnan J, Cheng C-H. Multi-period planning and un-certainty issues in cellular manufacturing: A review and future directions. European Journal of Operational Research. 2007; 177: 281–309p.

Chen M. A model for integrated production planning in cellular manufacturing systems. Integrated Manufacturing Systems. 2001; 12: 275–84p.

Olorunniwo F-O. Changes in production planning and control systems with implementation of cellular manufacturing. Production and Inventory Management. 1996; 37: 65–70p.

Benjaafar S, Sheikhzadeh M. Design of flexible plant layouts. IIE Transactions. 2000; 32: 309–22p.

Vakharia AJ, Moily JP, Huang Y. Evaluating virtual cells and multistage flow shops: An analytical approach. International Journal of Flexible Manufacturing Systems. 1999; 11: 291–314p.

Venkatadri U, Rardin RL, Montreuil B. A design methodology for fractal layout organization. IIE Transactions. 1997; 29: 911–24p.

Askin RG, Ciarallo FW, Lundgren NH. An empirical evaluation of holonic and fractal layouts. International Journal of Production Research. 1999; 37(5): 961–78p.

Chen M. A mathematical programming model for system reconfiguration in a

dynamic cellular manufacturing environment. Annals of Operations Research. 1998; 77: 109–28p.

Heragu S-S, Chen J-S. Optimal solution of cellular manufacturing system design: Bender’s decomposition approach. European Journal of Operational Research. 1998; 107: 175–92p.

Shang J-S, Tadikamalla P-R. Multicriteria design and control of a cellular manufacturing system through simulation and optimization. International Journal of Production Research. 1998; 36: 1515–29p.

Shinn A, Williams T. A stitch in time: a simulation of cellular manufacturing. Production and Inventory Management Journal. 1998; 39: 72–7p.

Petrov V. Flow Line Group Production Planning. Business Publications, London; 1968.

Hyer NL, Wemmerlo¨v, U. MRP/GT: A framework for production planning and control of cellular manufacturing. Decision Sciences. 1982; 13: 681–701p.

Dale BG, Russell D. Production control systems for small group production. Omega. 1983; 11(2): 175–85p.

Wemmerlov U. Production Planning and Control Procedures for Cellular Manufacturing. American Production and Inventory Control Society, Falls Church; 1988.

Askin RG, Mitwasi MG. Integrating facility layout with process selection and capacity planning. European Journal of Operational Research. 1992; 57: 162–73p.

Habich M. Koordination autonomer Fertigungsinseln durch ein adaptiertes PPSKonzept. Zeitschrift fu¨r wirtschaftliche Fertigung. 1989; 84(2): 74–7p.

Rohloff M. Decentralized production planning and design of a production management system based on an object-oriented architecture. International Journal of Production Economics. 1993; 30–1p, 365–83p.

Banerjee SK. Methodology for integrated manufacturing planning and control systems design, 54–88. In: Artiba A, Elmaghraby SE. (Eds). The Planning and Scheduling of Production Systems, Methodologies and Applications.

Journal of Production Research & Management

Volume 4, Issue 2

ISSN: 2249-4766 (online), ISSN: 2347-9930 (print)

JoPRM (2014) 12-30 © STM Journals 2014. All Rights Reserved Page 30

Chapman & Hall, London; 1997.

Schaller J-E, Selc-uk Erengu¨c-, S, Vakharia A-J. A methodology for integrating cell formation and production planning in cellular manufacturing. Annals of Operations Research. 1998; 77: 1–21p.

Chen M, Cao D. Coordinating production planning in cellular manufacturing environment using tabu search. Computers & Industrial Engineering. 2004; 46: 571–88p.

Defersha FM, Chen M. A comprehensive mathematical model for the design of cellular manufacturing systems. International Journal of Production Economics. 2006b; 103: 767–83p.

Nomden G, Van der Zee D-J. Virtual cellular manufacturing: configuring routing flexibility. International Journal of Production Economics. 2008; 112: 439–51p.

Ioannou G. Time-phased creation of hybrid manufacturing systems. International Journal of Production Economics. 2006; 102: 183–98p.

Kioon S-A, Bulgak A-A, Bektas T. Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration. European Journal of Operational Research. 2009; 192: 414–28p.

Mungwattana A. Design of Cellular Manufacturing Systems for Dynamic and Uncertain Production Requirements with the Presence of Routing Flexibility. PhD Thesis. Submitted to the Faculty of the Virginia Polytechnic Institute and State University, Blackburg, VA. 2000.

Tavakkoli-Moghaddam R, Aryanezhad MB, Safaei N, et al. solving a dynamic cell formation problem using meta-heuristics. Applied Mathematics and Computation. 2005; 170(2): 761–80p.




DOI: https://doi.org/10.37591/joprm.v4i2.7156

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