Dependability Measures Estimation Using Binomial Failure Rate Model

Abstract

Dependability of multi-component systems is highly impacted by common cause failures, what necessitates the appropriate consideration of such events in the dependability modeling process. This paper is dedicated to study the application of the binomial failure rate model in handling the contribution of common cause failures to estimate two key dependability indicators, namely: unavailability and unconditional failure intensity, using fault tree analysis with the probabilistic treatment of the associated parameter uncertainty. The results of such application are thoroughly compared to those of the traditional Beta factor model to highlight the possible differences.