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A Study of the Impact of Predictive Maintenance Parameters on the Improvment of System Monitoring

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  • Rim Louhichi

    (CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), Univeristé de Technologie de Compiègne, CS 60 319, 60203 Compiègne, France)

  • Mohamed Sallak

    (CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), Univeristé de Technologie de Compiègne, CS 60 319, 60203 Compiègne, France
    These authors contributed equally to this work.)

  • Jacques Pelletan

    (Institut Louis Bachelier, Université Paris 8, 28 Place de la Bourse, 75002 Paris, France
    These authors contributed equally to this work.)

Abstract

Predictive maintenance can be efficiently improved by studying the sensitivity of the maintenance decisions with respect to changes in the proposed model parameters (costs, duration of reparation, etc.). To address this issue, we first propose an original approach that includes both maintenance costs and maintenance risks in the same objective function to minimize. This approach uses the RUL as an indicator of the health state of the system and supposes that the system is under regular inspections and can only be replaced by a new system in case of serious deterioration or failure. Then, we present a process of human decision making under uncertainty based on several criteria. Finally, we study and analyze the influence of the model parameters and their implications on the obtained maintenance policies. The study will lead to some recommendations that can improve the predictive maintenance decisions and help experts better handle maintenance costs.

Suggested Citation

  • Rim Louhichi & Mohamed Sallak & Jacques Pelletan, 2022. "A Study of the Impact of Predictive Maintenance Parameters on the Improvment of System Monitoring," Mathematics, MDPI, vol. 10(13), pages 1-24, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2153-:d:843705
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    References listed on IDEAS

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    Cited by:

    1. Yi Chen & Xiaobing Ma & Fanping Wei & Li Yang & Qingan Qiu, 2022. "Dynamic Scheduling of Intelligent Group Maintenance Planning under Usage Availability Constraint," Mathematics, MDPI, vol. 10(15), pages 1-18, August.

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