Monitoring coefficient of variation using one-sided run rules control charts in the presence of measurement errors

Abstract

We investigate, in this paper, the effect of the measurement error (ME) on the performance of Run Rules control charts monitoring the coefficient of variation (CV) squared. The previous Run Rules CV chart in the literature is improved slightly by monitoring the CV squared using two one-sided Run Rules charts instead of monitoring the CV itself using a two-sided chart. The numerical results show that this improvement gives better performance in detecting process shifts. Moreover, we will show through simulation that the precision and accuracy errors do have a negative effect on the performance of the proposed Run Rules charts. We also find out that taking multiple measurements per item is not an effective way to reduce these negative effects. The proposed Run Rules control charts can be applied in the anomaly detection area.

Keywords: Markov chain; Run rules chart; anomaly detection; coefficient of variation; measurement errors.