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Time and cost constrained optimal designs of constant-stress and step-stress accelerated life tests

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  • Han, David

Abstract

By running life tests at higher stress levels than normal operating conditions, accelerated life testing quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. To conduct an accelerated life test efficiently with constrained resources in practice, several decision variables such as the sample allocation proportions and the stress durations should be determined carefully at the design stage. These decision variables affect not only the experimental cost but also the estimate precision of the lifetime parameters of interest. In this work, under the constraint that the total experimental cost does not exceed a pre-specified budget, the optimal decision variables are determined based on C/D/A-optimality criteria. In particular, the constant-stress and step-stress accelerated life tests are considered with the exponential failure data under time constraint as well. We illustrate the proposed methods using two real case studies, and under the identical budget constraint, the efficiencies of these two stress loading schemes are compared in terms of the ratio of optimal objective functions based on the information matrix.

Suggested Citation

  • Han, David, 2015. "Time and cost constrained optimal designs of constant-stress and step-stress accelerated life tests," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 1-14.
  • Handle: RePEc:eee:reensy:v:140:y:2015:i:c:p:1-14
    DOI: 10.1016/j.ress.2015.03.026
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    References listed on IDEAS

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    1. Dan Zhang & Haitao Liao, 2014. "Design of statistically and energy-efficient accelerated life testing experiments," IISE Transactions, Taylor & Francis Journals, vol. 46(10), pages 1031-1049, October.
    2. Elsayed, E.A. & Zhang, Hao, 2007. "Design of PH-based accelerated life testing plans under multiple-stress-type," Reliability Engineering and System Safety, Elsevier, vol. 92(3), pages 286-292.
    3. René Van Dorp, J. & Mazzuchi, Thomas A., 2005. "A general Bayes weibull inference model for accelerated life testing," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 140-147.
    4. Han, Donghoon & Balakrishnan, N., 2010. "Inference for a simple step-stress model with competing risks for failure from the exponential distribution under time constraint," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2066-2081, September.
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    Cited by:

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    2. Yin, Yi-Chao & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "An imprecise statistical method for accelerated life testing using the power-Weibull model," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 158-167.
    3. Qian, C. & Fan, X.J. & Fan, J.J. & Yuan, C.A. & Zhang, G.Q., 2016. "An accelerated test method of luminous flux depreciation for LED luminaires and lamps," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 84-92.
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    6. Abdullah AH Ahmadini & Frank PA Coolen, 2020. "Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test," Journal of Risk and Reliability, , vol. 234(2), pages 275-289, April.

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