Step-stress accelerated degradation test for Inverse Gaussian process based on M-optimality criterion

Step-Stress Accelerated Degradation Test (SSADT) has been extensively employed in reliability assessment of degradation-induced failure products, with growing attention focused on its optimal design. In this paper, the M-optimality criterion is applied to the optimal design of SSADT for Inverse Gaussian (IG) process. Different from the traditional optimization criteria that consider prediction accuracy or evaluation accuracy, this criterion takes minimizing the asymptotic variance of the Mechanism equivalence factor (Mef) as the objective function in order to improve the equivalence of failure mechanism. Using a widely used stress relaxation failure data set of electrical connectors, it is proved that compared with the traditional optimization criteria, the M-optimality criterion does not significantly reduce the model parameter estimation accuracy or product life prediction accuracy, but improves the failure mechanism equivalence.

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Publication Details

Journal
Scientific Reports
Published
2025-08-25
DOI
https://doi.org/10.1038/s41598-025-15171-w
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Step-stress accelerated degradation test for Inverse Gaussian process based on M-optimality criterion

Jia‐Yin Tang, Hao Zhou
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Scientific Reports
Reliability and Maintenance Optimization
article

Step-stress accelerated degradation test for Inverse Gaussian process based on M-optimality criterion

Jia‐Yin Tang, Hao Zhou
article en

Abstract

Step-Stress Accelerated Degradation Test (SSADT) has been extensively employed in reliability assessment of degradation-induced failure products, with growing attention focused on its optimal design. In this paper, the M-optimality criterion is applied to the optimal design of SSADT for Inverse Gaussian (IG) process. Different from the traditional optimization criteria that consider prediction accuracy or evaluation accuracy, this criterion takes minimizing the asymptotic variance of the Mechanism equivalence factor (Mef) as the objective function in order to improve the equivalence of failure mechanism. Using a widely used stress relaxation failure data set of electrical connectors, it is proved that compared with the traditional optimization criteria, the M-optimality criterion does not significantly reduce the model parameter estimation accuracy or product life prediction accuracy, but improves the failure mechanism equivalence.

Scientific ReportsVol. 15(1)
Southwest Jiaotong University (CN)
National Office for Philosophy and Social Sciences, National Social Science Fund of China
Openalex Percentile: Top 73%
Reliability and Maintenance Optimization
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