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Reliability demonstration methodology for products with Gamma Process by optimal accelerated degradation testing

Author

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  • Zhang, Chunhua
  • Lu, Xiang
  • Tan, Yuanyuan
  • Wang, Yashun

Abstract

For products with high reliability and long lifetime, accelerated degradation testing (ADT) may be adopted during product development phase to verify whether its reliability satisfies the predetermined level within feasible test duration. The actual degradation from engineering is usually a strictly monotonic process, such as fatigue crack growth, wear, and erosion. However, the method for reliability demonstration by ADT with monotonic degradation process has not been investigated so far. This paper proposes a reliability demonstration methodology by ADT for this kind of product. We first apply Gamma process to describe the monotonic degradation. Next, we present a reliability demonstration method by converting the required reliability level into allowable cumulative degradation in ADT and comparing the actual accumulative degradation with the allowable level. Further, we suggest an analytical optimal ADT design method for more efficient reliability demonstration by minimizing the asymptotic variance of decision variable in reliability demonstration under the constraints of sample size, test duration, test cost, and predetermined decision risks. The method is validated and illustrated with example on reliability demonstration of alloy product, and is applied to demonstrate the wear reliability within long service duration of spherical plain bearing in the end.

Suggested Citation

  • Zhang, Chunhua & Lu, Xiang & Tan, Yuanyuan & Wang, Yashun, 2015. "Reliability demonstration methodology for products with Gamma Process by optimal accelerated degradation testing," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 369-377.
  • Handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:369-377
    DOI: 10.1016/j.ress.2015.05.011
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    Cited by:

    1. Jianyu Xu & Qingpei Hu & Dan Yu & Min Xie, 2017. "Reliability demonstration test for load-sharing systems with exponential and Weibull components," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-19, December.
    2. Wang, Xiaofei & Wang, Bing Xing & Hong, Yili & Jiang, Pei Hua, 2021. "Degradation data analysis based on gamma process with random effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1200-1208.
    3. Wang, Huan & Wang, Guan-jun & Duan, Feng-jun, 2016. "Planning of step-stress accelerated degradation test based on the inverse Gaussian process," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 97-105.
    4. Sun, Bo & Fan, Xuejun & Ye, Huaiyu & Fan, Jiajie & Qian, Cheng & van Driel, Williem & Zhang, Guoqi, 2017. "A novel lifetime prediction for integrated LED lamps by electronic-thermal simulation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 14-21.
    5. Zheng, Huiling & Yang, Jun & Xu, Houbao & Zhao, Yu, 2023. "Reliability acceptance sampling plan for degraded products subject to Wiener process with unit heterogeneity," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    6. Yaping Li & Enrico Zio & Ershun Pan, 2021. "An MEWMA-based segmental multivariate hidden Markov model for degradation assessment and prediction," Journal of Risk and Reliability, , vol. 235(5), pages 831-844, October.
    7. Woo, Seong-woo & Pecht, Michael & O'Neal, Dennis L., 2020. "Reliability design and case study of the domestic compressor subjected to repetitive internal stresses," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Cheng, Yao & Liao, Haitao & Huang, Zhiyi, 2021. "Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    9. Kim, Seong-Joon & Mun, Byeong Min & Bae, Suk Joo, 2019. "A cost-driven reliability demonstration plan based on accelerated degradation tests," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 226-239.
    10. Sun, Bo & Fan, Xuejun & van Driel, Willem & Cui, Chengqiang & Zhang, Guoqi, 2018. "A stochastic process based reliability prediction method for LED driver," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 140-146.
    11. Dong, Qinglai & Cui, Lirong, 2019. "A study on stochastic degradation process models under different types of failure Thresholds," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 202-212.
    12. Huang, Jianlin & Golubović, Dušan S & Koh, Sau & Yang, Daoguo & Li, Xiupeng & Fan, Xuejun & Zhang, G.Q., 2016. "Lumen degradation modeling of white-light LEDs in step stress accelerated degradation test," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 152-159.

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