Performance comparison of generalized confidence interval and modified sampling distribution approaches for assessing one-sided capability indices with gauge measurement errors

Abstract

This study compares the performances of the generalized confidence interval (GCI) and the modified sampling distribution (MSD) approaches in evaluating the capability of processes with one-sided tolerance under the presence of gauge measurement errors (GME). The performance of both approaches are measured through a series of simulation. In terms of coverage rates (CRs), GCI and MSD approaches appear to work satisfactorily in the presence of GME since the CRs of the lower confidence bound with considering GME were all close to the nominal value. Furthermore, some of the coverage rates with considering the GME of GCI approach were smaller than those of MSD approach. GCI approach has better ability to assess process capability in the presence of GME. Based on numerical results, both approaches can be recommended to practitioners who assess process performances for cases with one-sided tolerance when GME is actually inevitable.