A reliability-growth model in a Bayes-decision framework

Market requirements demand testing programs in the development phase of complex repairable systems to be planned in order to improve system reliability. Thus, reliability-growth models are important. This paper proposes a nonparametric reliability-growth model which analyzes, in a Bayes-decision framework, failure data from repairable systems undergoing a Test-Find-Test growth program. The failure process in each stage of testing is assumed to follow a Power-Law process which can describe the failure pattern of systems subject to wear-out degradation during test. The mean number of failures in a prefixed time interval is used to measure the system reliability at each testing-stage, and the decision process is constructed around the posterior distribution of this quantity. A numerical example illustrates the decision process.