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Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system

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  • Boschian, V.
  • Rezg, N.
  • Chelbi, A.

Abstract

This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.

Suggested Citation

  • Boschian, V. & Rezg, N. & Chelbi, A., 2009. "Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1142-1149, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:1142-1149
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    References listed on IDEAS

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    1. Chelbi, Anis & Ait-Kadi, Daoud, 2004. "Analysis of a production/inventory system with randomly failing production unit submitted to regular preventive maintenance," European Journal of Operational Research, Elsevier, vol. 156(3), pages 712-718, August.
    2. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    3. Pintelon, L. M. & Gelders, L. F., 1992. "Maintenance management decision making," European Journal of Operational Research, Elsevier, vol. 58(3), pages 301-317, May.
    4. Percy, David F. & Kobbacy, Khairy A. H., 2000. "Determining economical maintenance intervals," International Journal of Production Economics, Elsevier, vol. 67(1), pages 87-94, August.
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    1. Roux, O. & Duvivier, D. & Quesnel, G. & Ramat, E., 2013. "Optimization of preventive maintenance through a combined maintenance-production simulation model," International Journal of Production Economics, Elsevier, vol. 143(1), pages 3-12.
    2. Fatemeh Moinian & Hamed Sabouhi & Jafar Hushmand & Ahmad Hallaj & Hiwa Khaledi & Mojtaba Mohammadpour, 2017. "Gas turbine preventive maintenance optimization using genetic algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 594-601, September.
    3. 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.
    4. A. Azadeh & M. Sheikhalishahi & S. Mortazavi & E. Ahmadi Jooghi, 2017. "Joint quality control and preventive maintenance strategy: a unique taguchi approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 123-134, March.

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