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Hierarchical decision making in production and repair/replacement planning with imperfect repairs under uncertainties

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

Abstract

In this paper, we analyse an optimal production, repair and replacement problem for a manufacturing system subject to random machine breakdowns. The system produces parts, and upon machine breakdown, either an imperfect repair is undertaken or the machine is replaced with a new identical one. The decision variables of the system are the production rate and the repair/replacement policy. The objective of the control problem is to find decision variables that minimize total incurred costs over an infinite planning horizon. Firstly, a hierarchical decision making approach, based on a semi-Markov decision model (SMDM), is used to determine the optimal repair and replacement policy. Secondly, the production rate is determined, given the obtained repair and replacement policy. Optimality conditions are given and numerical methods are used to solve them and to determine the control policy. We show that the number of parts to hold in inventory in order to hedge against breakdowns must be readjusted to a higher level as the number of breakdowns increases or as the machine ages. We go from the traditional policy with only one high threshold level to a policy with several threshold levels, which depend on the number of breakdowns. Numerical examples and sensitivity analyses are presented to illustrate the usefulness of the proposed approach.

Suggested Citation

  • Dehayem Nodem, F.I. & Kenne, J.P. & Gharbi, A., 2009. "Hierarchical decision making in production and repair/replacement planning with imperfect repairs under uncertainties," European Journal of Operational Research, Elsevier, vol. 198(1), pages 173-189, October.
    • Handle: RePEc:eee:ejores:v:198:y:2009:i:1:p:173-189
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    References listed on IDEAS

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    1. M. A. H. Dempster & M. L. Fisher & L. Jansen & B. J. Lageweg & J. K. Lenstra & A. H. G. Rinnooy Kan, 1981. "Analytical Evaluation of Hierarchical Planning Systems," Operations Research, INFORMS, vol. 29(4), pages 707-716, August.
    2. E. K. Boukas, 1998. "Hedging Point Policy Improvement," Journal of Optimization Theory and Applications, Springer, vol. 97(1), pages 47-70, April.
    3. Kenne, J.-P. & Gharbi, A. & Beit, M., 2007. "Age-dependent production planning and maintenance strategies in unreliable manufacturing systems with lost sale," European Journal of Operational Research, Elsevier, vol. 178(2), pages 408-420, April.
    4. Makis, Viliam & Jardine, Andrew K. S., 1993. "A note on optimal replacement policy under general repair," European Journal of Operational Research, Elsevier, vol. 69(1), pages 75-82, August.
    5. 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.
    6. Love, C. E. & Zhang, Z. G. & Zitron, M. A. & Guo, R., 2000. "A discrete semi-Markov decision model to determine the optimal repair/replacement policy under general repairs," European Journal of Operational Research, Elsevier, vol. 125(2), pages 398-409, September.
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    Cited by:

    1. 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.
    2. Xue, Guisen & Felix Offodile, O. & Zhou, Hong & Troutt, Marvin D., 2011. "Integrated production planning with sequence-dependent family setup times," International Journal of Production Economics, Elsevier, vol. 131(2), pages 674-681, June.
    3. Peng, Hao & van Houtum, Geert-Jan, 2016. "Joint optimization of condition-based maintenance and production lot-sizing," European Journal of Operational Research, Elsevier, vol. 253(1), pages 94-107.
    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. Azadegan, Arash & Porobic, Lejla & Ghazinoory, Sepehr & Samouei, Parvaneh & Saman Kheirkhah, Amir, 2011. "Fuzzy logic in manufacturing: A review of literature and a specialized application," International Journal of Production Economics, Elsevier, vol. 132(2), pages 258-270, August.
    6. Kenné, Jean-Pierre & Gharbi, Ali, 2018. "Production and replacement policies for a deteriorating manufacturing system under random demand and qualityAuthor-Name: Ouaret, Samir," European Journal of Operational Research, Elsevier, vol. 264(2), pages 623-636.
    7. 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.
    8. Kazaz, Burak & Sloan, Thomas W., 2013. "The impact of process deterioration on production and maintenance policies," European Journal of Operational Research, Elsevier, vol. 227(1), pages 88-100.

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