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PRM-based patterns for knowledge formalisation of industrial systems to support maintenance strategies assessment

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  • Medina-Oliva, G.
  • Weber, P.
  • Iung, B.

Abstract

The production system and its maintenance system must be now developed on “system thinking†paradigm in order to guarantee that Key Performance Indicators (KPI) will be optimized all along the production system (operation) life. In a recursive way, maintenance system engineering has to integrate also KPI considerations with regards to its own enabling systems. Thus this paper develops a system-based methodology wherein a set of KPIs is computed in order to verify if the objectives of the production and maintenance systems are satisfied. In order to help the decision-making process for maintenance managers, a “unified†generic model have been developed. This model integrates (a) the interactions of the maintenance system with its enabling systems, (b) the impact of the maintenance strategies through the computation of some key performance indicators, and (c) different kinds of knowledge regarding the maintenance system and the system of interest, including quantitative and qualitative knowledge. This methodology is based on an executable unified model built with Probabilistic Relational Model (PRM). PRM allows a modular representation and inferences computation of large size models. The methodology added-value is shown on a test-bench.

Suggested Citation

  • Medina-Oliva, G. & Weber, P. & Iung, B., 2013. "PRM-based patterns for knowledge formalisation of industrial systems to support maintenance strategies assessment," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 38-56.
    • Handle: RePEc:eee:reensy:v:116:y:2013:i:c:p:38-56
    DOI: 10.1016/j.ress.2013.02.026
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    References listed on IDEAS

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    Cited by:

    1. González, Esteban Le Maitre & Desforges, Xavier & Archimède, Bernard, 2018. "Assessment method of the multicomponent systems future ability to achieve productive tasks from local prognoses," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 403-415.
    2. Huang, Yeu-Shiang & Gau, Wei-Yo & Ho, Jyh-Wen, 2015. "Cost analysis of two-dimensional warranty for products with periodic preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 51-58.
    3. Edson Ruschel & Eduardo Alves Portela Santos & Eduardo de Freitas Rocha Loures, 2020. "Establishment of maintenance inspection intervals: an application of process mining techniques in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 53-72, January.

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