Optimal Sample Size Allocation for Accelerated Degradation Test Based on Wiener Process

Author(s):  
Sheng-Tsaing Tseng ◽  
Chih-Chun Tsai ◽  
N. Balakrishnan
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ping Qian ◽  
Lei Hong ◽  
Wenhua Chen ◽  
Yongwang Qian ◽  
Zhe Wang ◽  
...  

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.


2019 ◽  
Vol 12 (08) ◽  
pp. 1950086
Author(s):  
Carlos N. Bouza-Herrera ◽  
Sira M. Allende-Alonso ◽  
Gajendra K. Vishwakarma ◽  
Neha Singh

In many medical researches, it is needed to determine the optimal sample size allocation in a heterogeneous population. This paper proposes the algorithm for optimal sample size allocation. We consider the optimal allocation problem as an optimization problem and the solution is obtained by using Bisection, Secant, Regula–Falsi and other numerical methods. The performance of the algorithm for different numerical methods are analyzed and evaluated in terms of computing time, number of iterations and gain in accuracy using stratification. The efficacy of algorithm is evaluated for the response in terms of body mass index (BMI) to the dietetic supplement with diabetes mellitus, HIV/AIDS and cancer post-operatory recovery patients.


2017 ◽  
Vol 60 (1) ◽  
pp. 155-173 ◽  
Author(s):  
Pier Francesco Perri ◽  
María del Mar Rueda García ◽  
Beatriz Cobo Rodríguez

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