Abstract
At the research and development stage of a product, it is a great challenge for the manufacturer to select the most reliable design among several competing product designs which are highly reliable, since few (or even no) failures can be obtained by using traditional life tests or accelerated life tests. In such cases, if there exist product characteristics whose degradation over time can be related to reliability, then collecting degradation data can provide information about product reliability. This paper proposes a systematic approach to the selection problem with degradation data. First, an intuitively appealing selection rule is proposed, and then the optimal test plan is derived by using the criterion of minimizing the total experimental cost. The sample size, inspection frequency, and the termination time needed by the selection rule for each of the competing designs are computed by solving a nonlinear integer programming problem with a minimum probability of correct selection. Finally, an example is provided to illustrate the proposed method.
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