Detecting Changes in the Mean from Censored Lifetime Data

Abstract

In many industrial and medical applications observations are censored either due to inherent limitations or cost/time considerations. For example, with many products their lifetimes are sufficiently long that it is infeasible to test all products until failure even using accelerated testing. As a result, often a limited stress test is performed and only a proportion of the true failure times are observed. In such situations, it may be desirable to monitor the process quality using repeated lifetesting on samples of the process output. However, with highly censored observations a direct application of traditional monitoring procedures is not appropriate. In this article, Shewhart type control charts based on the conditional expected value weight are developed for monitoring processes where the censoring occurs at a fixed level. An example is provided to illustrate the application of this methodology.