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Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer

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  • Karamatsoukis, C.C.
  • Kyriakidis, E.G.

Abstract

We consider a manufacturing system in which an input generating installation transfers a raw material to a subsequent production unit. Both machines deteriorate stochastically with usage and may fail. For each machine the deteriorating process is described by some known transition probabilities between different degrees of deterioration. A buffer has been built between the two machines in order to cope with unexpected failures of the installation. A discrete-time Markov decision model is formulated for the optimal preventive maintenance of both machines. The maintenance times are geometrically distributed and the cost structure includes operating costs, storage costs, maintenance costs and costs due to the lost production. It is proved that for fixed buffer content and for fixed deterioration degree of one machine, the average-cost optimal policy initiates a preventive maintenance of the other machine if and only if its degree of deterioration exceeds some critical level. We study, by means of numerical results, the effect of the variation of some parameters on the optimal policy and on the minimum average cost. For the case in which the maintenance times follow continuous distributions, an approximate discrete-time Markov decision model is proposed.

Suggested Citation

  • Karamatsoukis, C.C. & Kyriakidis, E.G., 2010. "Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer," European Journal of Operational Research, Elsevier, vol. 207(1), pages 297-308, November.
  • Handle: RePEc:eee:ejores:v:207:y:2010:i:1:p:297-308
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    References listed on IDEAS

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    1. Karamatsoukis, C.C. & Kyriakidis, E.G., 2009. "Optimal maintenance of a production-inventory system with idle periods," European Journal of Operational Research, Elsevier, vol. 196(2), pages 744-751, July.
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    7. Dimitrakos, T.D. & Kyriakidis, E.G., 2008. "A semi-Markov decision algorithm for the maintenance of a production system with buffer capacity and continuous repair times," International Journal of Production Economics, Elsevier, vol. 111(2), pages 752-762, February.
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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. 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.
    3. van Oosterom, C.D. & Elwany, A.H. & Çelebi, D. & van Houtum, G.J., 2014. "Optimal policies for a delay time model with postponed replacement," European Journal of Operational Research, Elsevier, vol. 232(1), pages 186-197.
    4. Zheng, Meimei & Su, Zhiyun & Wang, Dong & Pan, Ershun, 2024. "Joint maintenance and spare part ordering from multiple suppliers for multicomponent systems using a deep reinforcement learning algorithm," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Zhang, Ning & Qi, Faqun & Zhang, Chengjie & Zhou, Hongming, 2022. "Joint optimization of condition-based maintenance policy and buffer capacity for a two-unit series system," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Yifan Zhou & Chao Yuan & Tian Ran Lin & Lin Ma, 2021. "Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers," Journal of Risk and Reliability, , vol. 235(3), pages 458-473, June.
    7. Xiao Wang & Hongwei Wang & Chao Qi, 2016. "Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 325-333, April.
    8. Zhou, Yifan & Li, Bangcheng & Lin, Tian Ran, 2022. "Maintenance optimisation of multicomponent systems using hierarchical coordinated reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    9. Zhou, Yifan & Guo, Yiming & Lin, Tian Ran & Ma, Lin, 2018. "Maintenance optimisation of a series production system with intermediate buffers using a multi-agent FMDP," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 39-48.
    10. Kiesmüller, G.P. & Sachs, F.E., 2020. "Spare parts or buffer? How to design a transfer line with unreliable machines," European Journal of Operational Research, Elsevier, vol. 284(1), pages 121-134.
    11. 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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