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Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems

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  • Dehayem Nodem, F.I.
  • Kenné, J.P.
  • Gharbi, A.

Abstract

This paper presents a method to find the optimal production, repair/replacement and preventive maintenance policies for a degraded manufacturing system. The system is subject to random machine failures and repairs. The status of the system is deemed to degrade with repair activities. When a failure occurs, the machine is either repaired or replaced, and a replacement action renews the machine, while a repair action brings it to a degraded operational state, with the next repair time increasing as the number of repairs increases as well. A preventive maintenance action is considered in order to improve the reliability of the machine, thereby reducing the amount of disruptions caused by machine failures. The decision variables are the production rate, the preventive maintenance rate and the repair/replacement switching policy upon machine failure. The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, preventive maintenance, inventory holding and backlog costs over an infinite planning horizon. The proposed model is based on a semi-Markov decision process, and the stochastic dynamic programming method is used to obtain the optimality conditions. A numerical example is given to illustrate the proposed model, and a sensitivity analysis is considered in order to confirm the structure of the control policy and to illustrate the usefulness of the proposed approach.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:134:y:2011:i:1:p:271-282
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    Cited by:

    1. Zhong, Chongquan & Jin, Haibo, 2014. "A novel optimal preventive maintenance policy for a cold standby system based on semi-Markov theory," European Journal of Operational Research, Elsevier, vol. 232(2), pages 405-411.
    2. Polotski, V. & Kenne, J.-P. & Gharbi, A., 2019. "Joint production and maintenance optimization in flexible hybrid Manufacturing–Remanufacturing systems under age-dependent deterioration," International Journal of Production Economics, Elsevier, vol. 216(C), pages 239-254.
    3. Behnamfar, Reza & Sajadi, Seyed Mojtaba & Tootoonchy, Mahshid, 2022. "Developing environmental hedging point policy with variable demand: A machine learning approach," International Journal of Production Economics, Elsevier, vol. 254(C).
    4. 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.
    5. Vladimir Polotski & Jean-Pierre Kenne & Ali Gharbi, 2019. "Optimal production and corrective maintenance in a failure-prone manufacturing system under variable demand," Flexible Services and Manufacturing Journal, Springer, vol. 31(4), pages 894-925, December.
    6. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean-Pierre & Montaño-Arango, Oscar & Hernandez-Gress, Eva Selene, 2016. "Production control problem integrating overhaul and subcontracting strategies for a quality deteriorating manufacturing system," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 134-150.
    7. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean-Pierre & Montaño-Arango, Oscar & Hernández-Gress, Eva Selene, 2018. "Subcontracting strategies with production and maintenance policies for a manufacturing system subject to progressive deterioration," International Journal of Production Economics, Elsevier, vol. 200(C), pages 103-118.
    8. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean Pierre, 2013. "Joint production and major maintenance planning policy of a manufacturing system with deteriorating quality," International Journal of Production Economics, Elsevier, vol. 146(2), pages 575-587.
    9. Zied Hajej & Nidhal Rezg & Tarek Askri, 2020. "Joint optimization of capacity, production and maintenance planning of leased machines," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 351-374, February.
    10. Kumar, Sameer & Yang, Muer & Goldschmidt, Kyle H., 2018. "Will aging voting machines cause more voters to experience long waits?," International Journal of Production Economics, Elsevier, vol. 198(C), pages 1-10.
    11. Wakiru, James M. & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K., 2019. "A simulation-based optimization approach evaluating maintenance and spare parts demand interaction effects," International Journal of Production Economics, Elsevier, vol. 208(C), pages 329-342.
    12. 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.
    13. Gössinger, Ralf & Helmke, Hanna & Kaluzny, Michael, 2017. "Condition-based release of maintenance jobs in a decentralised production-maintenance system – An analysis of alternative stochastic approaches," International Journal of Production Economics, Elsevier, vol. 193(C), pages 528-537.
    14. Edson Ruschel & Eduardo Alves Portela Santos & Eduardo de Freitas Rocha Loures, 2020. "Establishment of maintenance inspection intervals: an application of process mining techniques in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 53-72, January.
    15. Park, J.H. & Chang, Woojin & Lie, C.H., 2012. "Stress-reducing preventive maintenance model for a unit under stressful environment," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 42-48.

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