Abstract
A modular method, based on Binary Decision Diagrams and Bayesian Networks, is proposed to analyze system reliability. A fault tree is divided into independent subtrees using a very efficient linear time algorithm. Different solution techniques are applied to each subtree depending on the latter's characteristics, Binary Decision Diagrams solution for static fault trees, and Bayesian Networks solution for dynamic fault trees. The solutions of various independent subtrees are integrated to obtain the reliability of urban mass transit vehicles. The modular method, based on based on Binary Decision Diagrams and Bayesian Networks, can overcome main shortcomings of Markov Chains, and is useful for assessing the reliability of large and complex systems.
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