Bayesian networks in reliability modeling and assessment of multi-state systems

Abstract

Multi-state is a characteristic of advanced engineering systems and products. The reliability of multi-state systems (MSSs) has been received considerable attentions since the middle of 1970s. Over the last decade, Bayesian networks (BNs), as an effective and efficient reasoning tool under uncertainty, have been intensively concerned in MSS reliability modeling and assessment. This chapter presented a holistic framework for MSS reliability modeling and assessment by BNs. Firstly, the basic characteristics of MSSs and BNs are reviewed. Secondly, the detailed procedures of constructing the BN models of diverse MSSs are provided. The corresponding dynamic Bayesian network (DBN) models are also constructed to characterize the degradation profiles of MSSs over time, as well as various dependencies among components. Thirdly, a reliability assessment method by fusing multi-level observation data is developed. The results show that the reliability modeling and assessment for MSSs by BNs are effective considerably.