Reliability modeling of hierarchical systems is significantly difficult because of the complex system structures and imbalanced reliability information at different system levels. A Bayesian network reliability analysis methodology was proposed to model the reliability of binary-state hierarchical systems considering the combination of Bayesian network and Bayesian information aggregation approach to represent the failure relationship among system elements. An example illustrated that

the proposed methodology can significantly improve the accuracy of system-level reliability modeling and reduce the variances of the posterior failure distribution of system by considering the cascading failure dependency and utilizing all available reliability information throughout the system.