Abstract
Today’s free market is very competitive. In order to compete with others, it is a great challenge for the manufactures to design an optimal burn-in policy to eliminate failure or weak components before their products are shipped to the market. Without removing these defective products, the warranty and replacement costs will increase substantially. The burn-in policy is conventionally based on the formulation of a mixture of two lifetime distributions. For highly-reliable products, it is not easy to obtain their lifetime distributions within a short time of life-testing. Instead, if there exists a quality characteristic whose degradation over time can be closely related with the product’s lifetime, then we can construct optimal burn-in policy based on suitable degradation models. Recently, Tseng and Tang (2001) and Tseng, Tang, and Ku (2003) proposed two optimal burn-in policies (which are essentially based on the choices of the different window size) to screen out the defective products. However, there is no suitable literature to compare the performance of these two burn-in policies. Focusing on the setting of window size 2, this study demonstrates that these two approaches are essentially the same under some specific conditions. Furthermore, under more general parameter settings, we use numerical computations and graphical approach to compare the performance of these approaches. The results demonstrate that the policy proposed by Tseng, Tang, and Ku (2003) is always better than that of Tseng and Tang (2001). More specifically, among all the parameter settings in this study, the ability of reducing total misclassification probabilities up to 0.5% is around 10%. Note that the former one, however, requires a complex computational effort to obtain its screening procedure. Therefore, we recommend to using the later one if these two policies did not have significant differences in their screening performance.