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An ontology model for maintenance strategy selection and assessment

Author

Listed:
  • Juan José Montero Jiménez

    (ISAE-SUPAERO, Université de Toulouse
    TEC-Tecnológico de Costa Rica)

  • Rob Vingerhoeds

    (ISAE-SUPAERO, Université de Toulouse)

  • Bernard Grabot

    (ENIT-INP Toulouse)

  • Sébastien Schwartz

    (ISAE-SUPAERO, Université de Toulouse)

Abstract

Within maintenance management activities, engineers need to select maintenance strategies so to carry out the technical maintenance actions. A single equipment is composed of several components with different failure modes. There should be a maintenance strategy for each of them; while some of the components can be run-to-failure applying corrective maintenance, some others cannot afford a failure, and preventive or predictive strategies should be implemented. Selecting and assessing maintenance strategies is a complex task for which information from many sources should be retrieved. Information from a Failure Mode, Effects and Criticality Analysis, a cost–benefit-risk analysis, Computational Maintenance Management Systems, is often used by engineers to select and assess maintenance strategies. A selected strategy is often not evaluated over time to check its effectiveness. The strategy may need adjustments or substituted by a more efficient one, for example, a condition-based strategy substituting a time-based one. To facilitate maintenance strategies selection and assessment, the current study proposes an Ontology model for Maintenance Strategy Selection and Assessment (OMSSA). OMSSA serves as a formal terminology framework in maintenance strategies that can be used to develop smart computational agents that can help in the decision-making process for selecting and assessing maintenance strategies. To facilitate its future reuse and integration with other ontologies in the industrial domain, OMSSA builds following the state-of-the-art in ontology development by using a top-level domain-neutral ontology, the Basic Formal Ontology.

Suggested Citation

  • Juan José Montero Jiménez & Rob Vingerhoeds & Bernard Grabot & Sébastien Schwartz, 2023. "An ontology model for maintenance strategy selection and assessment," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1369-1387, March.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:3:d:10.1007_s10845-021-01855-3
    DOI: 10.1007/s10845-021-01855-3
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    References listed on IDEAS

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    1. Asma Talhi & Virginie Fortineau & Jean-Charles Huet & Samir Lamouri, 2019. "Ontology for cloud manufacturing based Product Lifecycle Management," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2171-2192, June.
    2. Ikuobase Emovon & Rosemary A. Norman & Alan J. Murphy, 2018. "Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 519-531, March.
    3. Heravi, Bahareh Rahmanzadeh & Lycett, Mark & de Cesare, Sergio, 2014. "Ontology-based standards development: Application of OntoStanD to ebXML business process specification schema," International Journal of Accounting Information Systems, Elsevier, vol. 15(3), pages 275-297.
    4. Yuqian Lu & Hongqiang Wang & Xun Xu, 2019. "ManuService ontology: a product data model for service-oriented business interactions in a cloud manufacturing environment," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 317-334, January.
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