Abstract
One-shot device test data have attracted increased attention. The working condition of a one-shot device is unknown until testing the device. In this paper, we consider one-shot device test data with defects that are induced in a realistic manufacturing process. The maximum likelihood approach is proposed for estimating the mean-time-to-failure. In this study, masked data are also considered when we cannot distinguish whether a failed device is originally defective or not. A Monte Carlo simulation study is conducted to evaluate the impacts of the masking effect on the estimation under different settings. Some practical guidelines and recommendations are provided.
Published Version
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