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PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems

Author

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  • Abdenour Soualhi

    (Laboratoire LASPI, University Lyon, UJM-Saint Etienne, 42100 Saint-Etienne, France)

  • Mourad Lamraoui

    (Laboratoire LASPI, University Lyon, UJM-Saint Etienne, 42100 Saint-Etienne, France)

  • Bilal Elyousfi

    (Laboratoire LASPI, University Lyon, UJM-Saint Etienne, 42100 Saint-Etienne, France)

  • Hubert Razik

    (Laboratoire Ampère, University Lyon, 69007 Lyon, France)

Abstract

Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization. It allows for permanently monitoring the health of the system and provides operators and managers with relevant information to decide on actions to be taken to maintain the system in optimal operational conditions. This paper aims to present the emergence of the PHM thematically to describe the subjacent processes, particularly prognosis, how it supplies the different maintenance strategies and to explain the benefits that can be anticipated. More specifically, this paper establishes a state of the art in prognostic methods used today in the PHM strategy. In addition, this paper shows the multitude of possible prognostic approaches and the choice of one among them that will help to provide a framework for industrial companies.

Suggested Citation

  • Abdenour Soualhi & Mourad Lamraoui & Bilal Elyousfi & Hubert Razik, 2022. "PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems," Energies, MDPI, vol. 15(19), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:6909-:d:920806
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    References listed on IDEAS

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    Keywords

    PHM; prognosis; maintenance; RUL;
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