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Production and preventive maintenance control in a stochastic manufacturing system

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  • Song, Dong-Ping

Abstract

This paper considers the problem of production and preventive maintenance control in a stochastic manufacturing system. The system is subject to multiple uncertainties such as random customer demands, machine failure and repair, and stochastic processing times. A threshold-type policy is proposed to control the production rate and the preventive maintenance operation simultaneously. The explicit form of the stationary distribution of the system state is derived analytically and used to produce the formula for various steady-state performance measures. The optimal threshold values can then be obtained by optimising the relevant formula. Numerical examples demonstrate that the proposed threshold policy is indeed optimal or extremely close to the optimal policy in a range of scenarios.

Suggested Citation

  • Song, Dong-Ping, 2009. "Production and preventive maintenance control in a stochastic manufacturing system," International Journal of Production Economics, Elsevier, vol. 119(1), pages 101-111, May.
    • Handle: RePEc:eee:proeco:v:119:y:2009:i:1:p:101-111
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    References listed on IDEAS

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    1. E. K. Boukas, 1998. "Hedging Point Policy Improvement," Journal of Optimization Theory and Applications, Springer, vol. 97(1), pages 47-70, April.
    2. Gharbi, A. & Kenne, J. P., 2000. "Production and preventive maintenance rates control for a manufacturing system: An experimental design approach," International Journal of Production Economics, Elsevier, vol. 65(3), pages 275-287, May.
    3. Cavory, G. & Dupas, R. & Goncalves, G., 2001. "A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 135-146, December.
    4. Van der Duyn Schouten, F. A. & Vanneste, S. G., 1995. "Maintenance optimization of a production system with buffer capacity," European Journal of Operational Research, Elsevier, vol. 82(2), pages 323-338, April.
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    Cited by:

    1. Gao, Chunyan & Shen, Houcai & Cheng, T.C.E., 2010. "Order-fulfillment performance analysis of an assemble-to-order system with unreliable machines," International Journal of Production Economics, Elsevier, vol. 126(2), pages 341-349, August.
    2. Song Jiu, 2021. "A two-phase approach for integrating preventive maintenance with production and delivery in an unreliable coal mine," Journal of Heuristics, Springer, vol. 27(6), pages 991-1020, December.
    3. Alejandro Mac Cawley & Maximiliano Cubillos & Rodrigo Pascual, 2020. "A real options approach for joint overhaul and replacement strategies with mean reverting prices," Annals of Operations Research, Springer, vol. 286(1), pages 303-324, March.
    4. Kenné, Jean-Pierre & Dejax, Pierre & Gharbi, Ali, 2012. "Production planning of a hybrid manufacturing–remanufacturing system under uncertainty within a closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 135(1), pages 81-93.
    5. Dehayem Nodem, F.I. & Kenné, J.P. & Gharbi, A., 2011. "Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems," International Journal of Production Economics, Elsevier, vol. 134(1), pages 271-282, November.
    6. Maria Chiara Magnanini & Tullio Tolio, 2020. "Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 241-271, June.
    7. Fitouhi, Mohamed-Chahir & Nourelfath, Mustapha, 2012. "Integrating noncyclical preventive maintenance scheduling and production planning for a single machine," International Journal of Production Economics, Elsevier, vol. 136(2), pages 344-351.
    8. Annie Francie, Kouedeu & Jean-Pierre, Kenne & Pierre, Dejax & Victor, Songmene & Vladimir, Polotski, 2014. "Stochastic optimal control of manufacturing systems under production-dependent failure rates," International Journal of Production Economics, Elsevier, vol. 150(C), pages 174-187.

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