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Proceedings/Recueil Des Communications Année : 2015

Aggregating Probabilistic Models of Complex Multi-State Systems

Danioko Fadaba
  • Fonction : Auteur
Sid-Ali Addouche
Tchoffa David
  • Fonction : Auteur
Abderrahman El Mhamedi

Résumé

This paper proposes an aggregating method based on a bayesian approach to improve the continuity of service for complex multi-state systems into an industrial context. In the study of our "equivalent" model of a given machines con_guration, each machine is considered as one bayesian multi-state sub-model. A simulation is made with or no learning on the node of maintenance policy for each con_guration of machines in order to study, master its process of degradation and suggest the best actions of maintenance policy over an given exploitation phase with regard to the chosen performance indicators.

Dates et versions

hal-01230157 , version 1 (17-11-2015)

Identifiants

Citer

Danioko Fadaba, Sid-Ali Addouche, Tchoffa David, Abderrahman El Mhamedi. Aggregating Probabilistic Models of Complex Multi-State Systems. IFAC-PapersOnLine, 15th IFAC Symposium on “Information Control Problems in Manufacturing,INCOM 2015, 2015, Canada. 48 (3), pp.136-140, 2015, ⟨10.1016/j.ifacol.2015.06.071⟩. ⟨hal-01230157⟩
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