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Optimal design of accelerated destructive degradation tests with block effects

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  • Jiaxiang Cai
  • Zhi-Sheng Ye

Abstract

Accelerated Destructive Degradation Tests (ADDTs) are effective for reliability assessment of highly reliable products whose key performance characteristic has to be destructively measured. Test units in a reliability experiment typically share the same test environments, and this introduces block effects to the resulting ADDT data. Nevertheless, the block effects are seldom considered in the optimal design of an ADDT plan. Motivated by an application of a seal strength test, this study discusses methods for planning ADDT with block effects. In particular, two types of block effects are considered, i.e., the rig-layer blocking due to a shared test rig, and the gauge-layer blocking resulting from simultaneous measurements. The ADDT planning specifies the optimal stress levels and allocation of test units to these stress levels to minimize the asymptotic variance of the estimated lifetime quantiles at use conditions. The optimal test plans are investigated analytically and through a comprehensive numerical study. An application to the motivating example reveals the importance of considering the block effects in the test design.

Suggested Citation

  • Jiaxiang Cai & Zhi-Sheng Ye, 2021. "Optimal design of accelerated destructive degradation tests with block effects," IISE Transactions, Taylor & Francis Journals, vol. 54(1), pages 73-90, October.
    • Handle: RePEc:taf:uiiexx:v:54:y:2021:i:1:p:73-90
    DOI: 10.1080/24725854.2020.1849875
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    Cited by:

    1. Zhang, Aibo & Hao, Songhua & Li, Peng & Xie, Min & Liu, Yiliu, 2022. "Performance modeling for condition-based activation of the redundant safety system subject to harmful tests," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Luo, Yi & Zhao, Xiujie & Liu, Bin & He, Shuguang, 2024. "Condition-based maintenance policy for systems under dynamic environment," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    3. Li, Ting & He, Shuguang & Zhao, Xiujie, 2022. "Optimal warranty policy design for deteriorating products with random failure threshold," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    4. Duan, Chaoqun & Li, Yifan & Pu, Huayan & Luo, Jun, 2022. "Adaptive monitoring scheme of stochastically failing systems under hidden degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Wang, Jiaolong & Zhang, Fode & Zhang, Jianchuan & Liu, Wen & Zhou, Kuang, 2023. "A flexible RUL prediction method based on poly-cell LSTM with applications to lithium battery data," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    6. Chang, Miaoxin & Huang, Xianzhen & Coolen, Frank PA & Coolen-Maturi, Tahani, 2023. "New reliability model for complex systems based on stochastic processes and survival signature," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1349-1364.
    7. Fang, Guanqi & Pan, Rong & Wang, Yukun, 2022. "Inverse Gaussian processes with correlated random effects for multivariate degradation modeling," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1177-1193.
    8. Wu, Xin & Huang, Tingting & Liu, Jie, 2023. "Common stochastic effects induced multivariate degradation process with temporal dependency in degradation characteristic and unit dimensions," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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