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Optimal designs and reliability sampling plans for one-shot devices with cost considerations

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  • Wu, Shuo-Jye
  • Hsu, Chu-Chun
  • Huang, Syuan-Rong

Abstract

In this paper, we investigate some statistical inference, optimal design, and reliability sampling plan problems related to multiple constant-stress accelerated life test with one-shot device testing. At each stress-level combination, a generalized exponential lifetime distribution is considered. The scale parameter of the proposed distribution is assumed to be a log-linear function of stresses. To conduct a one-shot device accelerated life test more efficiently, one has to address the problem of determining optimal setting that produces the best estimation results. In practice, the experimental budget is always limited. The size of budget usually influences the decision of experimental setting and hence, influences the precision of estimation. Therefore, this paper is to determine the optimal experimental setting under D-optimality criterion with cost constraint. In addition, reliability sampling plan is an important statistical tool in the area of quality control. This paper is also to explore the optimal reliability sampling plan which minimizes the total experimental cost of a one-shot device accelerated life test with specified producer’s risk and consumer’s risk.

Suggested Citation

  • Wu, Shuo-Jye & Hsu, Chu-Chun & Huang, Syuan-Rong, 2020. "Optimal designs and reliability sampling plans for one-shot devices with cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832019309500
    DOI: 10.1016/j.ress.2020.106795
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    References listed on IDEAS

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    1. Ling, M.H. & Hu, X.W., 2020. "Optimal design of simple step-stress accelerated life tests for one-shot devices under Weibull distributions," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Chen, D.G. & Lio, Y.L., 2010. "Parameter estimations for generalized exponential distribution under progressive type-I interval censoring," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1581-1591, June.
    3. Cheng, Yao & Elsayed, Elsayed A., 2018. "Reliability modeling and optimization of operational use of one-shot units," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 27-36.
    4. Newby, Martin, 2008. "Monitoring and maintenance of spares and one shot devices," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 588-594.
    5. Balakrishnan, N. & Ling, M.H., 2014. "Gamma lifetimes and one-shot device testing analysis," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 54-64.
    6. Balakrishnan, N. & So, H.Y. & Ling, M.H., 2015. "EM algorithm for one-shot device testing with competing risks under exponential distribution," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 129-140.
    7. Yada Zhu & Elsayed A. Elsayed, 2013. "Design of accelerated life testing plans under multiple stresses," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(6), pages 468-478, September.
    8. Zhao, Qian Qian & Yun, Won Young, 2018. "Determining the inspection intervals for one-shot systems with support equipment," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 63-75.
    9. Yada Zhu & Elsayed Elsayed, 2013. "Optimal design of accelerated life testing plans under progressive censoring," IISE Transactions, Taylor & Francis Journals, vol. 45(11), pages 1176-1187.
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    Cited by:

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    4. Zhu, Xiaojun & Balakrishnan, N., 2022. "One-shot device test data analysis using non-parametric and semi-parametric inferential methods and applications," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

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