Accelerated degradation test planning and optimization

Abstract

With increasing emphasis on reliability in industry, products are now made more robust, and few failures are observed in a short development period. In this circumstance, assessing product reliability based on degradation data at high stress levels becomes necessary. These tests are called accelerated degradation tests. There is a need to scientifically design these test plans. A good test plan can save time and expense, and provide more accurate estimates of reliability for the same number of test units and test time. To address this problem, a four-step-approach for the optimum planning of accelerated degradation tests is proposed in this study. First, a cost model for accelerated degradation tests is given. New analytical methods for obtaining the optimal allocations of the test units to selected stress levels are developed next. The stress considered here is temperature. Then, measurement plans are discussed. Nonlinear mixed effects models are applied and further developed and extended to allow for acceleration in the analysis of accelerated degradation data and to obtain the degradation model's parameters. A simulation method is used to evaluate the test plans' properties. In the simulation step, the mean square error is used as a criterion for comparing the accuracies that can be obtained from the test plans. A linear degradation case is used to illustrate the given approach. An LED example is also given to illustrate this approach. Test plans for obtaining accurate estimates of reliability information within cost budgets are important. The proposed approach enables reliability and test engineers to get the most efficient use of their test resources.