In Statistical Process Control (SPC), the control charting technique is an effective method to solve quality issues in manufacturing and service industries. The R and S charts are commonly used to monitor the process variance in industries due to the charts’ simplicity and high sensitivity toward large shifts. However, these charts are not sensitive toward small and moderate shifts in the process variance. On the other hand, the more sophisticated charts, such as the exponentially weighted moving average (EWMA) S chart and the cumulative sum (CUSUM) S chart are very effective in detecting small changes in the process variance. However, most quality practitioners do not adopt these charts in real applications due to their design complexity. In view of this setback, the variable sampling interval (VSI) approach is incorporated into the run sum (RS) S chart, in order to suggest an effective, yet a simple chart, for detecting small, moderate and large shifts in the process variance. Apart from that, the coefficient of variation (CV) is an important quality characteristic to take into account when the process mean and standard deviation are not constant, even though the process is in-control
