Estimation of Multi-components System's reliability: Comparison of two Graphical Model Approaches

Reliability analysis is an integral part of system design and operating. Moreover, it can be an input to optimize maintenance policies. Recently, Bayesian Networks (BN) and Dynamic Bayesian Networks (DBN) have been proved relevant to represent complex systems and perform reliability studies. The major drawback of this approach comes from the constraint on the state sojourn times which are necessarily exponentially distributed, as in usual markovian approaches. Therefore, a new formalism was introduced to avoid this constraint: the Graphical Duration Models (GDM). This paper aims to quantify the reliability estimation error due to an exponential approximation when the system follows other kinds of sojourn time's distributions. Finally results obtained by DBN and GDM will be compared.