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A new universal multi-stress acceleration model and multi-parameter estimation method based on particle swarm optimization

Author

Listed:
  • Yao Liu
  • Yashun Wang
  • Zhengwei Fan
  • Xun Chen
  • Chunhua Zhang
  • Yuanyuan Tan

Abstract

High reliability and long-lifetime products usually work in multi-stress environment such as temperature, humidity, electricity, and vibration. How to evaluate the reliability of the product under multi-stress condition is an urgent problem to ensure the safe and reliable operation of the product. Accelerated test provides an efficient and feasible way; however, the existing acceleration models have some shortcomings, such as less stress type, neglecting the stress coupling, and multi-parameter estimation difficulties. Therefore, in this article, first, a new universal multi-stress acceleration model is derived based on the classical Arrhenius model. Second, a multi-parameter estimation method for multi-stress model is proposed by combining particle swarm optimization and maximum likelihood estimation. Six simulation cases are used to verify the effectiveness of the proposed multi-parameter estimation method. The results of Case 1 to Case 3 show that the maximum mean square error of five parameters in the multi-stress model without considering stress coupling is 3.71%. The results of Case 4 to Case 6 show that the maximum mean square error of nine parameters in the multi-stress model considering stress coupling is 7.69%. Finally, an application example is performed to investigate the performance of the universal multi-stress acceleration model and multi-parameter estimation method.

Suggested Citation

  • Yao Liu & Yashun Wang & Zhengwei Fan & Xun Chen & Chunhua Zhang & Yuanyuan Tan, 2020. "A new universal multi-stress acceleration model and multi-parameter estimation method based on particle swarm optimization," Journal of Risk and Reliability, , vol. 234(6), pages 764-778, December.
    • Handle: RePEc:sae:risrel:v:234:y:2020:i:6:p:764-778
    DOI: 10.1177/1748006X20918793
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    References listed on IDEAS

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    2. Wu, Shuo-Jye & Huang, Syuan-Rong, 2017. "Planning two or more level constant-stress accelerated life tests with competing risks," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 1-8.
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    Cited by:

    1. Liu, Yao & Wang, Yashun & Fan, Zhengwei & Bai, Guanghan & Chen, Xun, 2021. "Reliability modeling and a statistical inference method of accelerated degradation testing with multiple stresses and dependent competing failure processes," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Ekene Gabriel Okafor & Whit Vinson & David Ryan Huitink, 2023. "Effect of Stress Interaction on Multi-Stress Accelerated Life Test Plan: Assessment Based on Particle Swarm Optimization," Sustainability, MDPI, vol. 15(4), pages 1-26, February.
    3. Ye, Xuerong & Hu, Yifan & Zheng, Bokai & Chen, Cen & Zhai, Guofu, 2022. "A new class of multi-stress acceleration models with interaction effects and its extension to accelerated degradation modelling," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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