Title of article :
Using probabilistic relational models for knowledge representation of production systems: A new approach to assessing maintenance strategies
Author/Authors :
Iung، نويسنده , , Benoît and Medina-Oliva، نويسنده , , Gabriela and Weber، نويسنده , , Philippe and Levrat، نويسنده , , Eric، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
4
From page :
419
To page :
422
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) 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 system-based 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.
Keywords :
Maintenance , Performance , decision-making
Journal title :
CIRP Annals - Manufacturing Technology
Serial Year :
2012
Journal title :
CIRP Annals - Manufacturing Technology
Record number :
2269599
Link To Document :
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