Bayesian networks and probability boxes to model uncertainty in unavailability assessment

Abstract

In this paper the problem of uncertainty in assessing unavailability of Safety Instrumented Systems (SIS) is treated. The characteristic parameters of the SIS including Common Cause Failure (CCF) factors are replaced by probability densities families (p-boxes) allowing reliability experts to express their uncertainty on the statement of values probabilities. We show how the imprecision is modelled and propagated in a Bayesian networks which induces uncertainty about the failure probability on demand of the SIS and its Safety Integrity Level (SIL). We will demonstrate how the uncertainty in the values of some characteristic parameters causes significant variations in the level risk.