Optimal design of accelerated degradation test based on the combination forecast method for products with uncertain degradation models

Abstract

The optimal design of an accelerated degradation test can effectively shorten the test duration and improve the accuracy of lifetime evaluation. This article proposes a new optimization method that considers the uncertainty of degradation models during the optimal design, and with the application of the combination forecast method based on the Akaike information criterion, establishes the optimization objective. Furthermore, the total test time is limited, with the inspection interval and the number of inspections as the design variables. A numerical example is presented to verify the effectiveness of the proposed method. The results show that when the degradation models of products are uncertain in the optimal design, the proposed method can be effectively used to obtain the optimum test plan; this makes an important contribution to reliability tests and assessment. Finally, a sensitivity analysis is conducted to assess the robustness of the optimum plan on parameter variation.