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Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles

Author

Listed:
  • Bouvard, K.
  • Artus, S.
  • Bérenguer, C.
  • Cocquempot, V.

Abstract

This paper aims at presenting a method to optimize the maintenance planning for a commercial heavy vehicle. Such a vehicle may be considered as a multi-components system. Grouping maintenance operations related to each component reduces the global maintenance cost of the system. Classically, the optimization problem is solved using a priori reliability characteristics of components. Two types of methods may be used, i.e. static or dynamic methods. Static methods provide a fixed maintenance planning, whereas dynamic methods redefine the groups of maintenance operations at each decision time. Dynamic procedures can incorporate component information such as component states or detected failures. For deteriorating systems, reliability characteristics of each component may be estimated thanks to deterioration models and may be updated when a degradation measure is available. This additional information on degradation features allows to better follow the real state of each component and to improve the maintenance planning.

Suggested Citation

  • Bouvard, K. & Artus, S. & Bérenguer, C. & Cocquempot, V., 2011. "Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles," Reliability Engineering and System Safety, Elsevier, vol. 96(6), pages 601-610.
  • Handle: RePEc:eee:reensy:v:96:y:2011:i:6:p:601-610
    DOI: 10.1016/j.ress.2010.11.009
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    References listed on IDEAS

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    1. G Budai & D Huisman & R Dekker, 2006. "Scheduling preventive railway maintenance activities," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1035-1044, September.
    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. Rommert Dekker & Ralph Wildeman & Frank Duyn Schouten, 1997. "A review of multi-component maintenance models with economic dependence," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 45(3), pages 411-435, October.
    4. Wildeman, R. E. & Dekker, R. & Smit, A. C. J. M., 1997. "A dynamic policy for grouping maintenance activities," European Journal of Operational Research, Elsevier, vol. 99(3), pages 530-551, June.
    5. Crespo Marquez, Adolfo & Gupta, Jatinder N.D., 2006. "Contemporary maintenance management: process, framework and supporting pillars," Omega, Elsevier, vol. 34(3), pages 313-326, June.
    6. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    7. van der Duyn Schouten, F. A. & Vanneste, S. G., 1990. "Analysis and computation of (n, N)-strategies for maintenance of a two-component system," European Journal of Operational Research, Elsevier, vol. 48(2), pages 260-274, September.
    8. Cho, Danny I. & Parlar, Mahmut, 1991. "A survey of maintenance models for multi-unit systems," European Journal of Operational Research, Elsevier, vol. 51(1), pages 1-23, March.
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