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

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  • Bae, Suk Joo
  • Yuan, Tao
  • Ning, Shuluo
  • Kuo, Way

Abstract

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.

Suggested Citation

  • Bae, Suk Joo & Yuan, Tao & Ning, Shuluo & Kuo, Way, 2015. "A Bayesian approach to modeling two-phase degradation using change-point regression," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 66-74.
    • Handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:66-74
    DOI: 10.1016/j.ress.2014.10.009
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ling, M.H. & Ng, H.K.T. & Tsui, K.L., 2019. "Bayesian and likelihood inferences on remaining useful life in two-phase degradation models under gamma process," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 77-85.
    2. Gao, Hongda & Cui, Lirong & Dong, Qinglai, 2020. "Reliability modeling for a two-phase degradation system with a change point based on a Wiener process," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Hu, Changhua & Xing, Yuanxing & Du, Dangbo & Si, Xiaosheng & Zhang, Jianxun, 2023. "Remaining useful life estimation for two-phase nonlinear degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
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    5. Wang, Pingping & Tang, Yincai & Joo Bae, Suk & He, Yong, 2018. "Bayesian analysis of two-phase degradation data based on change-point Wiener process," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 244-256.
    6. Wen, Yuxin & Wu, Jianguo & Das, Devashish & Tseng, Tzu-Liang(Bill), 2018. "Degradation modeling and RUL prediction using Wiener process subject to multiple change points and unit heterogeneity," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 113-124.
    7. Hongyu Wang & Xiaobing Ma & Yu Zhao, 2020. "Bayesian inference for a novel hierarchical accelerated degradation model considering the mechanism variation," Journal of Risk and Reliability, , vol. 234(5), pages 708-720, October.
    8. Liu, Di & Wang, Shaoping, 2021. "An artificial neural network supported stochastic process for degradation modeling and prediction," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    9. Yuan, Tao & Wu, Xinying & Bae, Suk Joo & Zhu, Xiaoyan, 2019. "Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 157-164.
    10. Zhu, Xiaoyan & Hao, Yaqian, 2021. "Component rearrangement and system replacement for a system with stochastic degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    11. Kim, Seong-Joon & Mun, Byeong Min & Bae, Suk Joo, 2019. "A cost-driven reliability demonstration plan based on accelerated degradation tests," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 226-239.
    12. Wang, Jun & Zhu, Xiaoyan, 2021. "Joint optimization of condition-based maintenance and inventory control for a k-out-of-n:F system of multi-state degrading components," European Journal of Operational Research, Elsevier, vol. 290(2), pages 514-529.
    13. Peng, Weiwen & Li, Yan-Feng & Mi, Jinhua & Yu, Le & Huang, Hong-Zhong, 2016. "Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 75-87.
    14. Wang, Lizhi & Pan, Rong & Wang, Xiaohong & Fan, Wenhui & Xuan, Jinquan, 2017. "A Bayesian reliability evaluation method with different types of data from multiple sources," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 128-135.
    15. Chen, Zhen & Li, Yaping & Zhou, Di & Xia, Tangbin & Pan, Ershun, 2021. "Two-phase degradation data analysis with change-point detection based on Gaussian process degradation model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    16. Zhao, Xiujie & Chen, Piao & Gaudoin, Olivier & Doyen, Laurent, 2021. "Accelerated degradation tests with inspection effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1099-1114.
    17. Sun, Xuxue & Mraied, Hesham & Cai, Wenjun & Zhang, Qiong & Liang, Guoyuan & Li, Mingyang, 2018. "Bayesian latent degradation performance modeling and quantification of corroding aluminum alloys," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 84-96.

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