Assessing process performance with incapability index based on multiple samples

Abstract

The process incapability index, which provides an uncontaminated separation between information concerning the process accuracy and the process precision, has been introduced to provide quantitative measures on process performance. Contributions based on a single sample of the estimated incapability index have been proposed extensively. In this paper, estimation of the incapability index based on multiple samples is considered for normally distributed processes. The uniformly minimum variance unbiased estimator (UMVUE) is derived. Upper confidence limits based on the UMVUE are constructed. A useful procedure for judging whether the process satisfies the preset quality reliability requirement is also proposed for practitioners to use.