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A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction

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  • Song, Kai
  • Cui, Lirong

Abstract

Due to the complex structures and the multi-functionality of modern products, there are usually two or more performance characteristics which can reflect a product’s degradation states. The degradation processes corresponding to these performance characteristics are dependent in general, which brings challenges to the degradation data analysis. In this paper, a gamma process based degradation model is developed for the bivariate dependent degradation data, where the dependency between the two degradation processes is captured by a common random effect naturally. The expectation maximization algorithm is employed to estimate the model parameters. Then, a real-time prediction method for a product’s remaining useful life is proposed using the Bayesian method. Finally, both the simulation study and the case study are provided for illustration, whose results demonstrate that the proposed model as well as the corresponding inference methods does work well.

Suggested Citation

  • Song, Kai & Cui, Lirong, 2022. "A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021006797
    DOI: 10.1016/j.ress.2021.108200
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    References listed on IDEAS

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