RELIABILITY MODELLING WITH DYNAMIC BAYESIAN NETWORKS

Abstract: Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance strategies. The work reported here presents a methodology for developing Dynamic Bayesian Networks (DBN) to formalise such complex dynamic models. A small valve system then is used to compare the reliability estimations obtained by the proposed DBN model and by the classical Markov Chain