Reliability modeling and a statistical inference method of accelerated degradation testing with multiple stresses and dependent competing failure processes

Yao Liu, Yashun Wang, Zhengwei Fan, Guanghan Bai and Xun Chen

Reliability Engineering and System Safety, 2021, vol. 213, issue C

Abstract: In this paper, a multiple stresses reliability model with dependent competing failure processes (DCFPs) is proposed, which includes constructing the multiple stresses acceleration model and deriving the degradation-shock dependences competing model. The multiple stresses coupling are considered in multiple stresses acceleration model, and the degradation-shock dependence is considered and modeled by Facilitation model. Then, a statistical inference method of accelerated degradation testing with multiple stresses and dependent competing failure processes is proposed. Finally, a practical example is used to demonstrate accuracy of the proposed model and method. It is shown that the reliability model without considering multiple environment stresses is a special case (40°C, 65%RH and random shocks) of that considering multiple environment stresses. We also explain the phenomenon that the reliability at same time is lower with the larger temperature, larger humidity and more random shock due to that the mean of wear rate is larger with the larger stress, and the reliability is lower with the larger mean of wear rate. Moreover, the maximum MSE of the parameter estimation result obtained by the statistical inference method is 0.34%.

Keywords: Multiple stresses; Dependent competing failure processes; Accelerated degradation testing; Reliability modeling; Statistical inference method (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021001897

DOI: 10.1016/j.ress.2021.107648

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