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

•A reliability model with multiple stresses and multiple failure processes is proposed.•A statistical inference method of ATD with multiple stresses is proposed.•Practical example is used to demonstrate accuracy of the model and method. In this paper, a multiple stresses reliability model with depen...

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Published inReliability engineering & system safety Vol. 213; p. 107648
Main Authors Liu, Yao, Wang, Yashun, Fan, Zhengwei, Bai, Guanghan, Chen, Xun
Format Journal Article
LanguageEnglish
Published Barking Elsevier Ltd 01.09.2021
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Abstract •A reliability model with multiple stresses and multiple failure processes is proposed.•A statistical inference method of ATD with multiple stresses is proposed.•Practical example is used to demonstrate accuracy of the model and method. 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%.
AbstractList 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%.
•A reliability model with multiple stresses and multiple failure processes is proposed.•A statistical inference method of ATD with multiple stresses is proposed.•Practical example is used to demonstrate accuracy of the model and method. 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%.
ArticleNumber 107648
Author Wang, Yashun
Liu, Yao
Bai, Guanghan
Fan, Zhengwei
Chen, Xun
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Keywords Accelerated degradation testing
Multiple stresses
Statistical inference method
Reliability modeling
Dependent competing failure processes
Language English
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Snippet •A reliability model with multiple stresses and multiple failure processes is proposed.•A statistical inference method of ATD with multiple stresses is...
In this paper, a multiple stresses reliability model with dependent competing failure processes (DCFPs) is proposed, which includes constructing the multiple...
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StartPage 107648
SubjectTerms Accelerated degradation testing
Accelerated tests
Degradation
Dependent competing failure processes
Failure
Mathematical models
Model accuracy
Multiple stresses
Parameter estimation
Reliability
Reliability analysis
Reliability engineering
Reliability modeling
Statistical inference
Statistical inference method
Stresses
Wear rate
Title Reliability modeling and a statistical inference method of accelerated degradation testing with multiple stresses and dependent competing failure processes
URI https://dx.doi.org/10.1016/j.ress.2021.107648
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Volume 213
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