In monitoring the coefficient of variation (CV), the variable sampling interval (VSI) type charts are a useful adaptive strategy that has been recently combined with various types of charts, including exponentially weighted moving average (EWMA) and variable sample size (VSS) charts. These combinations lead to desirable control charts with an impressive performance in detecting process shifts or anomalies. However, in these studies, the authors asserted that adaptive type charts are not competitive to monitor downward shifts in the CV. Therefore, they willingly omitted the decrease in process shifts. In this paper, we suggest overcoming this downside by designing two one-sided VSI CUSUM control charts for tracking the CV. The performance of the proposed charts is evaluated by the average time to signal (ATS) criterion. The numerical results show that our proposed adaptive type charts are efficient charts to monitor downward shifts in the CV.

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.