A Bayesian approach to modeling two-phase degradation using change-point regression

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초록

Influenced by defects or contaminants remaining after a series of manufacturing processes, the degradation paths of some products exhibit two-phase patterns over the testing period. This paper proposes a hierarchical Bayesian change-point regression model to fit the two-phase degradation patterns, and derives the failure-time distribution of a unit that is randomly selected from its population. A Gibbs sampling algorithm is developed for the inference of the parameters in the change-point degradation model, as well as for the prediction of the failure-time distribution of the randomly selected unit The proposed approach is applied to the degradation paths of plasma display panels (PDPs) presenting the two-phase pattern.

키워드

Degradation modelingChange-point regressionFailure-time distributionGibbs samplingHierarchical Bayesian modelingINVERSE GAUSSIAN PROCESSTO-FAILURE DISTRIBUTIONBURN-INMAINTENANCERELIABILITYSIGNALS
제목
A Bayesian approach to modeling two-phase degradation using change-point regression
저자
Bae, Suk JooYuan, TaoNing, ShuluoKuo, Way
DOI
10.1016/j.ress.2014.10.009
발행일
2015-02
유형
Article
저널명
Reliability Engineering and System Safety
134
페이지
66 ~ 74