Search

In this article, the population reliability modeling and individual residual life prediction are discussed. Firstly, three kinds of different Wiener process models are used to characterize the degradation data, and the unknown parameters are estimated by using the Markov Chain Monte Carlo (MCMC) method. Secondly, under those degradation models, the individual residual life prediction method is also obtained on the basis of current degradation quantity. Finally, a fatigue cracks data example is given to illustrate the usefulness and validity of the proposed model and method. Numerical results show that the random effect model is well fitted with the actual degradation data, and this model has smallest prediction error. Meanwhile the prediction accuracy is acceptable, and this prediction method provides a foundation for maintenance decision. [ABSTRACT FROM AUTHOR]