Dependability Modelling of Repairable Systems using Bayesian Networks

We present a Hybrid Bayesian Network (HBN) framework to model the availability of renewable systems. We use an approximate inference algorithm for HBNs that involves dynamically discretizing the domain of all continuous variables and use this to obtain accurate approximations for the renewal or repair time distributions for a system. We show how we can use HBNs to model corrective repair time, logistics delay times and scheduled maintenance time distributions and combine these with time to failure distributions to derive system availability. Example models are presented and are accompanied by detailed descriptions of how repair (renewal) distributions might be modelled using HBNs.