Monitoring Processes with Highly Censored Data

Abstract

The need for process monitoring in industry is ubiquitous. By monitoring process output, process changes may be rapidly detected and problems corrected. However, in many industrial and medical applications, observations are censored due to either inherent limitations or cost/time considerations. For example, when testing breaking strengths or failure times, often a limited stress test is performed and only a small proportion of the true failure strengths or failure times are observed. With highly censored observations, a direct application of traditional monitoring procedures is not appropriate. In this article, Shewhart-type X̄ and S control charts based on the conditional expected value weight are suggested for monitoring processes where the censoring occurs at a fixed level. We provide an example to illustrate the application of this methodology.

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