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Optimizing Processing Rates for Flexible Manufacturing Systems

Author

Listed:
  • Paul J. Schweitzer

    (William E. Simon Graduate School of Business Administration, University of Rochester, Rochester, New York 14627)

  • Abraham Seidmann

    (William E. Simon Graduate School of Business Administration, University of Rochester, Rochester, New York 14627)

Abstract

This paper introduces the generic concept of processing rates as decision variables in Flexible Manufacturing Systems (FMS's). The objective is to determine the minimum cost processing rates given the FMS throughput target, the work-in-process level, part routes, transporter delays, and the variable capacity cost function for each machine. A nonlinear Mean Value Analysis queueing network optimization methodology is developed to control bottlenecks and queue lengths as the processing rates are varied. This methodology further provides the average and marginal unit production costs along with necessary and sufficient feasibility conditions for the FMS throughput targets. Industrial sample data is then used to illustrate the solution of the optimal tool speed problem in a metal-cutting FMS. Considerable cost savings are demonstrated using the proposed methodology in contrast with the conventional one-machine optimization models. Several economic insights regarding the issues of capacity allocation for FMS's, and a generalization of the square root capacity allocation rule for closed networks of queues, are also presented.

Suggested Citation

  • Paul J. Schweitzer & Abraham Seidmann, 1991. "Optimizing Processing Rates for Flexible Manufacturing Systems," Management Science, INFORMS, vol. 37(4), pages 454-466, April.
    • Handle: RePEc:inm:ormnsc:v:37:y:1991:i:4:p:454-466
    DOI: 10.1287/mnsc.37.4.454
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    Citations

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    Cited by:

    1. Herbon, Avi, 2020. "An approximated solution to the constrained integrated manufacturer-buyer supply problem," Operations Research Perspectives, Elsevier, vol. 7(C).
    2. Bintong Chen & Charles L. Munson, 2004. "Resource allocation with lumpy demand: To speed or not to speed?," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(3), pages 363-385, April.
    3. Kim, Taebok & Glock, Christoph H., 2018. "Production planning for a two-stage production system with multiple parallel machines and variable production rates," International Journal of Production Economics, Elsevier, vol. 196(C), pages 284-292.
    4. Sana, S. & Goyal, S. K. & Chaudhuri, K. S., 2004. "A production-inventory model for a deteriorating item with trended demand and shortages," European Journal of Operational Research, Elsevier, vol. 157(2), pages 357-371, September.
    5. Sana, Shib Sankar & Goyal, Suresh Kumar & Chaudhuri, Kripasindhu, 2007. "An imperfect production process in a volume flexible inventory model," International Journal of Production Economics, Elsevier, vol. 105(2), pages 548-559, February.
    6. Sodhi, Manbir S. & Lamond, Bernard F. & Gautier, Antoine & Noel, Martin, 2001. "Heuristics for determining economic processing rates in a flexible manufacturing system," European Journal of Operational Research, Elsevier, vol. 129(1), pages 105-115, February.
    7. Glock, Christoph H. & Grosse, Eric H., 2021. "The impact of controllable production rates on the performance of inventory systems: A systematic review of the literature," European Journal of Operational Research, Elsevier, vol. 288(3), pages 703-720.
    8. Koulamas, Christos P., 1995. "Simultaneous determination of the cutting speed and lot size values in machining systems," European Journal of Operational Research, Elsevier, vol. 84(2), pages 356-370, July.
    9. Sohani, Sahar & Barman, Tuli & Sarkar, Biswajit & Gunasekaran, Angappa & Pareek, Sarla, 2024. "Retail management policy through firefly algorithm under uncertainty using Dempster-Shafer theory for production firm," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    10. Khouja, Moutaz, 1997. "The scheduling of economic lot sizes on volume flexible production systems," International Journal of Production Economics, Elsevier, vol. 48(1), pages 73-86, January.
    11. Subba Rao, S. & Gunasekaran, A. & Goyal, S. K. & Martikainen, T., 1998. "Waiting line model applications in manufacturing," International Journal of Production Economics, Elsevier, vol. 54(1), pages 1-28, January.
    12. Heike, G. & Ramulu, M. & Sorenson, E. & Shanahan, P. & Moinzadeh, K., 2001. "Mixed model assembly alternatives for low-volume manufacturing: The case of the aerospace industry," International Journal of Production Economics, Elsevier, vol. 72(2), pages 103-120, July.
    13. Chandrashekar, Ashok & Callarman, Thomas E., 1998. "A modelling study of the effects of continuous incremental improvement in the case of a process shop," European Journal of Operational Research, Elsevier, vol. 109(1), pages 111-121, August.
    14. Refael Hassin & Yair Y. Shaki & Uri Yovel, 2015. "Optimal service‐capacity allocation in a loss system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(2), pages 81-97, March.
    15. J. Smith, 2015. "Optimal workload allocation in closed queueing networks with state dependent queues," Annals of Operations Research, Springer, vol. 231(1), pages 157-183, August.

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