On planning accelerated life tests for comparing two product designs

Accelerated life test (ALT) planning is one of the most important and challenging tasks for reliability engineers. Since the late 1970s, methods for efficient ALT planning have been studied extensively and over 150 research papers have been published [1]. Most of the existing methods focus on designing tests to minimize the estimation precision of model parameters or their functions. Popularly used test designs such as the 2-level statistically optimum plan, 3-level best compromise plan and 3-level best standard plan are all based on this theory. However, although these designs are very useful for estimating distribution parameters or given reliability metrics, they are not efficient for planning tests that compare different products. In this paper, we will present two methods for designing ALT to compare two different designs in terms of their B10 life. The probability of detecting a given amount of difference of the B10 lives is the focus of the proposed methods. This probability usually is called detection power. Comparing the estimated lives of two designs is the same as comparing two random variables since each life estimated through the ALT data is a random variable. According to the required detection probability, the sample size of a comparison test can be determined by either the analytical or the simulation method given in this paper. An example is used in the paper to illustrate the theory and the applications of the proposed me thods. The presented methods are general methods and can be extended to other situations and applied beyond the example used in this paper.