Failure Importance Analysis and Adjustment Based on Bayesian Networks

Importance measures in reliability engineering are used to find the weak areas of a system. Traditional importance measures for binary systems and multi-state systems mainly concern reliability importance of an individual component, and seldom consider the reliability importance of the causal components. This paper constructs the failure importance analysis Bayesian networks (FIABN) to describe the causality system firstly. Then we present the failure importance measures models for binary and multi-state systems based on FIABN. Finally, the adjustment methods of the failure importance are given. The numerical simulations show failure importance measures models and adjustment methods are effective.