Affiliations: Unité de Recherche LARA Automatique, Ecole Nationale d'Ingénieurs de Tunis, le Belvédère, Tunis, Tunisie | Laboratoire d'Automatique, Génie Informatique et Signal, Ecole Centrale de Lille, Cité Scientifique, Villeneuve d'Ascq, France | Evaluation and Safety of Automated Transport Systems, French institute of science and technology for transport, development and networks, Villeneuve d'Ascq, France
Note: [] Corresponding author. A. Mhalla, Unité de Recherche LARA Automatique, Ecole Nationale d'Ingénieurs de Tunis, BP 37, le Belvédère, 1002 Tunis, Tunisie. E-mails: anis.mhalla@enim.rnu.tn. (A. Mhalla); simon.collart_dutilleul@ec-lille.fr. (S.C. Dutilleul); etienne.craye@ec-lille.fr. (E. Craye); mohamed.benrejeb@enit.rnu.tn. (M. Benrejeb)
Abstract: In conventional fault tree analysis, probabilities of the basic events were treated as precise values; sometimes this probability does not correspond to real situations of systems because of ambiguity and the imprecision of some basic events. In order to overcome this disadvantage, a new fuzzy probabilistic method, based on the fuzzy set theory and the Buckley approach, is used in the fault tree analysis for quantifying the basic event uncertainty. According to failure modes, a fault tree of a milk manufacturing unit is constructed. Failure in the milk manufacturing workshop is analysed using the proposed method.
Keywords: Failure rates, fuzzy probabilities, milk production unit, fault tree, uncertainty, diagnosis, maximum time constraints
