Article Dans Une Revue CIRP Annals - Manufacturing Technology Année : 2012

Using probabilistic relational models for knowledge representation of production systems: A new approach to assessing maintenance strategies

Résumé

The production system and its maintenance system must be now developed on ''system thinking'' paradigm in order to guarantee that key performance indicators (KPI) expected 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 systembased methodology wherein a set of KPIs is computed to conclude on the assessing of maintenance strategies. This methodology is based on an executable unified model built with Probabilistic Relational Model. The methodology added-value is shown on a test-bench.

Dates et versions

hal-00705485 , version 1 (07-06-2012)

Identifiants

Citer

Benoît Iung, Gabriela Medina-Oliva, Philippe Weber, Eric Levrat. Using probabilistic relational models for knowledge representation of production systems: A new approach to assessing maintenance strategies. CIRP Annals - Manufacturing Technology, 2012, 61 (1), pp.419-422. ⟨10.1016/j.cirp.2012.03.059⟩. ⟨hal-00705485⟩
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