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Preventive Maintenance Models: A Review

In: Replacement Models with Minimal Repair

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  • Shaomin Wu

    (Cranfield University)

Abstract

Preventive maintenance (PM) is the maintenance carried out at predetermined intervals or according to prescribed criteria and intended to reduce the probability of failure or the degradation of the functioning of an item. When designing maintenance policies for complex systems, a common process is to adopt a top-down methodology : selection of a maintenance strategy such as RCM (reliability centered maintenance), TPM (total productive maintenance), and RBM (risk based maintenance), and then selection of maintenance policy such as condition-based maintenance and PM. In the entire process, PM models, which can be used to estimate not only the effectiveness of the PM but also some reliability indices such as time to failure, play an important role. In the literature, a number of PM models have been proposed to measure PM effectiveness, considering different applications. This paper first presents a brief review on PM strategies, and then reviews existing PM models.

Suggested Citation

  • Shaomin Wu, 2011. "Preventive Maintenance Models: A Review," Springer Series in Reliability Engineering, in: Lotfi Tadj & M.-Salah Ouali & Soumaya Yacout & Daoud Ait-Kadi (ed.), Replacement Models with Minimal Repair, pages 129-140, Springer.
    • Handle: RePEc:spr:ssrchp:978-0-85729-215-5_4
    DOI: 10.1007/978-0-85729-215-5_4
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    Cited by:

    1. Theissler, Andreas & Pérez-Velázquez, Judith & Kettelgerdes, Marcel & Elger, Gordon, 2021. "Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Wenke Gao, 2020. "An extended geometric process and its application in replacement policy," Journal of Risk and Reliability, , vol. 234(1), pages 88-103, February.
    3. Dewan, Isha & Dijoux, Yann, 2015. "Modelling repairable systems with an early life under competing risks and asymmetric virtual age," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 215-224.

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