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Maintenance modeling and optimization integrating human and material resources

Author

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  • Martorell, S.
  • Villamizar, M.
  • Carlos, S.
  • Sánchez, A.

Abstract

Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

Suggested Citation

  • Martorell, S. & Villamizar, M. & Carlos, S. & Sánchez, A., 2010. "Maintenance modeling and optimization integrating human and material resources," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1293-1299.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:12:p:1293-1299
    DOI: 10.1016/j.ress.2010.06.006
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    Citations

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    Cited by:

    1. Wang, Wenbin, 2011. "A joint spare part and maintenance inspection optimisation model using the Delay-Time concept," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1535-1541.
    2. Reder, Maik & Yürüşen, Nurseda Y. & Melero, Julio J., 2018. "Data-driven learning framework for associating weather conditions and wind turbine failures," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 554-569.
    3. Hao Li & Shanghua Mi & Qifeng Li & Xiaoyu Wen & Dongping Qiao & Guofu Luo, 2020. "A scheduling optimization method for maintenance, repair and operations service resources of complex products," Journal of Intelligent Manufacturing, Springer, vol. 31(7), pages 1673-1691, October.
    4. Bjarnason, Erik T.S. & Taghipour, Sharareh & Banjevic, Dragan, 2014. "Joint optimal inspection and inventory for a k-out-of-n system," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 203-215.

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