Multi-objective optimization design of accelerated degradation test based on Wiener process

Abstract

A multi-objective optimization method for the accelerated degradation test based on Wiener process is proposed in this article in order to solve the problem that a single objective optimization cannot solve the difficulty or even conflicting test configurations caused by different optimization objective functions. An accelerated degradation model is established based on Wiener process, and the unknown parameters are solved by a two-step maximum likelihood estimation method. Considering both the accuracies of life estimation and the model parameter estimation, a multi-objective optimization model is established with the optimization goals of the minimum asymptotic variance of P-quantile of lifetime and the maximum determinant of Fisher information matrix. The Pareto solutions are set by the multi-objective genetic algorithm, and the test configurations for multi-objectives are obtained. Under the step stress accelerated degradation test and the constant stress accelerated degradation test, the effectiveness of the proposed method is verified by an optimization example of LEDs accelerated degradation test.

Keywords:

• Wiener process
• accelerated degradation test
• multi-objective optimization
• genetic algorithm
• maximum likelihood estimation

Data availability

The simulation study and illustrative example data used to support the findings of this study are included within the article.

Additional information

Funding

The authors are grateful for the financial support from the National Natural Science Foundation of China [No. 51875499].