A New BDD Algorithm for Fault Tree Analysis

Abstract

FTA is a NP-hard problem. When using the Binary Decision Diagram (BDD) to analyze a fault tree, the size of the BDD transformed by the fault tree increases as the number of basic events increases. When using the BDD method to analyze a large-scale fault tree, there is not enough memory to store the resulting BDD structure, and the process of obtaining the minimum cut set is time consuming. This paper introduces a simplified BDD (SimBDD) structure to solve these problems. SimBDD is a BDD whose scale linearly relates to the number of basic events in the fault tree. Therefore, when using this structure to deal with large fault tree, the structure is small and easy to store. The number of paths in SimBDD is small and the minimum cut set gets faster.