Abstract
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.
Highlights
With the rapid development of modern science and technology, many products with high reliability and long life have emerged in the fields of machinery, electronics, aerospace, etc., which makes it more difficult for engineers to obtain enough failure data in a reasonable and effective time.erefore, an accelerated degradation test (ADT) method is developed, which studies the product performance degradation process and extrapolates the reliability measure of products by statistical analysis of the degradation data and solves the reliability evaluation problem under lack of failure data or no failure data
Whitmore [2] established a degradation model that takes into account the randomness of performance degradation and measurement error. e randomness of performance degradation is described by Wiener process, and the randomness of measurement error is described by normal distribution
When the product performance degradation process is as nonlinear Wiener process, Liao and Tseng [4] provided the optimal step-stress accelerated degradation test plans by minimizing the asymptotic variance of the estimated 100pth percentile of the product’s lifetime distribution under constraints on the total cost
Summary
With the rapid development of modern science and technology, many products with high reliability and long life have emerged in the fields of machinery, electronics, aerospace, etc., which makes it more difficult for engineers to obtain enough failure data in a reasonable and effective time. When the performance degradation model obeys the linear Wiener process, the related work can be referred to [19, 20] With the minimum cost as the optimization goal, Tang [19] proposed a step accelerated degradation test plan considering the evaluation accuracy. When the product performance degradation process is as nonlinear Wiener process, Liao and Tseng [4] provided the optimal step-stress accelerated degradation test plans by minimizing the asymptotic variance of the estimated 100pth percentile of the product’s lifetime distribution under constraints on the total cost. Tsai et al [22] provided the optimal design plans for degradation tests based on a Gamma degradation process with random effects by minimizing the asymptotic variance of the estimate of the 100pth percentile of the lifetime distribution of the product under the constraint that the total experimental cost does not exceed a prespecified budget.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call