Bayesian Reliability Analysis of Complex Series/Parallel Systems of Binomial Subsystems and Components

Abstract

A Bayesian procedure is presented for estimating the reliability (or availability) of a complex system of independent binomial series or parallel subsystems and components. Repeated identical components or subsystems are also permitted. The method uses either test or prior data (perhaps both or neither) at the system, subsystem, and component levels. Beta prior distributions are assumed throughout. The method is motivated and illustrated by the following problem. It is required to estimate the unavailability on demand of the low-pressure coolant injection system in a certain U.S. commercial nuclear-power boiling-water reactor. Three data sources are used to calculate the posterior distribution of the overall system demand unavailability from which the required estimates are obtained. The sensitivity of the results to the three data sources is examined. A FORTRAN computer program for implementing the procedure is available.