Application of importance measures to transport industry: Computation using Bayesian networks and Fault Tree Analysis

Importance measures are useful in the identification of components, which are most effective towards safety improvement. This paper will summarize a number of Component Importance Measures (CIM), computation of the CIM using Fault Tree Analysis (FTA) and Bayesian Networks (BNs) will be investigated for the transport industry. The BNs are directed acyclic probabilistic graphical models, used for joint distribution of random variables in a concise and efficient way. The BNs have several advantages over classical ways like FTA.