Bayesian network for the characterization of faults in a multivariate process

Abstract : 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.
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Communication dans un congrès
11th International Conference on Quality and Dependability (CCF'08), 2008, Sinaia, Romania. 2008
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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. 2008. 〈inria-00517026〉

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