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Bayes Decision Analysis of Reliability Growth for a Repairable System
Published March 16, 1994 by Associazione Tecnica Dell'Automobile in Italy
The increasing market requirements demand testing programs in the developmental phase of complex repairable systems, such as modern engines, to be planned to improve system reliability. Thus, reliability growth models have been object of a great deal of research in recent years.
In this paper a nonparametric reliability growth model is proposed in a Bayesian decision framework, in order to analyze failure data of 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 allows the failure pattern of systems subject to wear-out degradation during testing to be described. The expected number of failures in a prefixed time interval is used to measure the system reliability at each stage of testing and the decision process is constructed around the posterior density on this quantity.
A numerical example is given, to illustrate the proposed decision process.