An Optimal Adaptive Variable Sample Size Scheme for the Multivariate Coefficient of Variation

Development of an efficient process monitoring system has always received great attention. Previous studies revealed that the coefficient variation (CV) is important in ensuring quality, especially for a where its mean and variance are highly correlated. The fact almost all industrial involves minimum two or more related quality characteristics being monitored simultaneously, this paper incorporates salient feature adaptive sample size VSS scheme into standard multivariate CV (MCV) chart, called MCV chart. A Markov chain model developed derivation chart’s performance measures, i.e average run length (ARL), deviation (SDRL), (ASS), number observations to signal (ANOS) expected (EARL). numerical comparison shows proposed chart prevails over existing detecting small moderate upward downward shifts.