Measurement Plan Optimization for Degradation Test Design based on the Bivariate Wiener Process

2013 ◽  
Vol 30 (8) ◽  
pp. 1215-1231 ◽  
Author(s):  
Guang Jin ◽  
David Matthews
Keyword(s):  
Wiener Process ◽  
Test Design ◽  
Measurement Plan ◽  
Plan Optimization ◽  
Bivariate Wiener Process ◽  
Degradation Test

scholarly journals Optimization of the Accelerated Degradation Test Plan for Electrical Connector Contact Pairs Based on a Nonlinear Wiener Process

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ping Qian ◽  
Lei Hong ◽  
Wenhua Chen ◽  
Yongwang Qian ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Wiener Process ◽  
Stress Level ◽  
Test Plan ◽  
Accelerated Degradation ◽  
Stress Levels ◽  
Degradation Test ◽  
Accelerated Degradation Test ◽  
Stress Dependent ◽  
Drift Coefficient

Accelerated degradation test is an effective method to evaluate the reliability of products with long life and high reliability. The performance of most products fluctuates randomly in the degradation process, so it is suitable to use Wiener process. At present, the diffusion coefficient is regarded as constant in Wiener process, while the drift coefficient is related to stress. However, in practice, the amplitude of product performance fluctuation increases with the increase of stress level, which is not constant. Therefore, for the nonlinear Wiener case where both the drift coefficient and the diffusion coefficient are stress dependent, this paper studies the constant-stress accelerated degradation test theories and methods. Taking the contact pairs of electrical connectors as the research object, the minimum variance of reliable life estimate under normal stress is taken as the target. After determining the censored time at each stress level, the test stress level, the sample distribution ratio at each stress level, and the test interval at the one-third power scale of time are taken as design variables. The test plan under 3, 4, and 5 stress levels is optimized and compared with the general test plan. The influence of the difference between high and low stress levels on the evaluation accuracy is analyzed. Finally, the sensitivity analysis of parameters shows that the optimization plan has good robustness, and the change of stress quantity has little influence on the robustness of the plan.

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