IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v54y2021i1p73-90.html
   My bibliography  Save this article

Optimal design of accelerated destructive degradation tests with block effects

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24725854.2020.1849875
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24725854.2020.1849875?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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).
    3. 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.
    4. 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).
    5. 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.
    6. 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).
    7. 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).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:54:y:2021:i:1:p:73-90. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.