Assessing process performance based on the incapability index C-pp

Abstract

Process incapability index C-pp has been introduced to the manufacturing industry to measure process performance. But all existing methods for testing C-pp require further estimation of the distribution parameters when calculating the p-values and critical values causing additional sampling errors, which is unreliable. In this paper, an efficient SAS computer program is provided to calculate the p-values. Extensive calculations were performed to examine the behavior of the p-values and the critical values c(0) against the distribution parameter. Useful critical values for commonly used capability requirements are also tabulated. A simple but practical step-by-step hypothesis-testing procedure is developed for in-plant applications. Significance: Complicated statistical theory for the uniformly minimum variance unbiased estimator (UMVUE) of C-pp is implemented for testing normal processes. An efficient computer program and useful critical values are given. A practical procedure is developed for the practitioners to determine whether their process meets the preset capability requirement. Since the proposed procedure does not require further estimation of the distribution parameter, the decisions made are more reliable than that using other approaches.