A progressive approach for the detection of the coefficient of variation

Abstract

AbstractA progressive average chart usually triggers initial out‐of‐control (OC) signals more simply and quickly than other memory‐type charts . In this paper, two progressive average control procedures are proposed for monitoring the coefficient of variation (CV) of a normally distributed process variable, namely, the progressive CV (PCV) and progressive resetting CV (PRCV) control charts , respectively. The implementation of the proposed charts is presented, and the necessary design parameters are provided. Through extensive numerical simulations, it is shown that the proposed PCV and PRCV charts outperform several existing control charts to detect the initial OC signals, especially for the small and moderate CV shifts, under each combination of the shift size, the sample size, and the in‐control target value of the CV. In addition, the application of the proposed control charts is illustrated by a detection example for a spinning process.