A nonparametric-Bayes reliability-growth model

The authors propose a nonparametric reliability-growth model based on Bayes analysis techniques. By using the unique properties of the assumed prior distributions, the moments of the posterior distribution of the failure rate at various stages during a development test can be found. The proposed model is compared with the US Army Material Systems Analysis Activity (AMSAA) model based on relative and mean-square prediction errors. In all but one circumstance, the proposed model performed better than either the AMSAA or nonparametric models. The one exception appears to be when no information about the failure rate is available at the start of test and the actual failure process is nonhomogeneous Poisson, with power-law intensity function, as assumed by the AMSAA model.<>