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Reliability estimation for one-shot devices under cyclic accelerated life-testing

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  • Zhu, Xiaojun
  • Liu, Kai
  • He, Mu
  • Balakrishnan, N.

Abstract

A one-shot device, like an automobile airbag, is a product or an equipment that can be used only once. Better quality and longer lifetime of one-shot devices nowadays increase the cost of life test experiment under normal operating condition. Cyclic stress test, adopted in life-testing experiments by increasing stress levels to induce more failures, has been used to investigate the reliability analysis of one-shot devices based on Coffin–Manson principle. However, the Coffin–Manson model only considers temperature change in each cycle. Moreover, it assumes that the reliability is independent of the cycling frequency, which may not be a realistic assumption in practice. Birnbaum–Saunders distribution, originally developed to model fatigue failure under cyclic loading, has been used widely to model lifetime data. As the Norris–Landzberg model is proposed for modeling fatigue life due to cyclic temperature fluctuation, it is used in this work together with Birnbaum–Saunders distribution for modeling lifetimes of one-shot devices under accelerated life-tests with different cyclic temperature fluctuations. It contains the Coffin–Manson model as a special case. Inferential methods for model parameters, reliability and mean lifetime are developed in this paper. Simulation study and model discrimination are carried out to evaluate the performance of the proposed model and inferential methods. Finally, an example is presented to illustrate the model and the inferential results developed here.

Suggested Citation

  • Zhu, Xiaojun & Liu, Kai & He, Mu & Balakrishnan, N., 2021. "Reliability estimation for one-shot devices under cyclic accelerated life-testing," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
  • Handle: RePEc:eee:reensy:v:212:y:2021:i:c:s095183202100140x
    DOI: 10.1016/j.ress.2021.107595
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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. Cheng, Yao & Elsayed, Elsayed A., 2017. "Reliability modeling of mixtures of one-shot units under thermal cyclic stresses," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 58-66.
    3. Newby, Martin, 2008. "Monitoring and maintenance of spares and one shot devices," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 588-594.
    4. Balakrishnan, N. & Ling, M.H., 2012. "EM algorithm for one-shot device testing under the exponential distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 502-509.
    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. Pan, Zhengqiang & Balakrishnan, Narayanaswamy, 2011. "Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 949-957.
    8. 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).
    9. N. Balakrishnan & Debasis Kundu, 2019. "Birnbaum‐Saunders distribution: A review of models, analysis, and applications," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(1), pages 4-49, January.
    10. 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.
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    Cited by:

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    3. 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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