Bayesian network for the characterization of faults in a multivariate process - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2008

Bayesian network for the characterization of faults in a multivariate process

Résumé

The main objective of this paper is to present a new method of detection and characterization with a bayesian network. For that, a combination of two original works is made. The first one is the work of Li et al. [1] who proposed a causal decomposition of the T² statistic. The second one is our previous work on the detection of fault with bayesian networks [2], [3], notably on the modelization of multivariate control charts in a bayesian network. Thus, in the context of multivariate processes, we propose an original network structure allowing deciding if a fault is appeared in the process. More, this structure permits the identification of the variables that are responsible (root causes) of the fault. A particular interest of the method is the fact that the detection and the identification can be made with a unique tool: a bayesian network.
Fichier principal
Vignette du fichier
verron08e.pdf (1.21 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

inria-00517026 , version 1 (13-09-2010)

Identifiants

  • HAL Id : inria-00517026 , version 1

Citer

Sylvain Verron, Teodor Tiplica, Abdessamad Kobi. Bayesian network for the characterization of faults in a multivariate process. 11th International Conference on Quality and Dependability (CCF'08), 2008, Sinaia, Romania. ⟨inria-00517026⟩

Collections

UNIV-ANGERS
68 Consultations
164 Téléchargements

Partager

Gmail Facebook X LinkedIn More