One of the most efficient tools of statistical process control is the control chart. The efficiency and effectiveness of control charts depend on its in-control robustness, i.e., how the control chart reacts against the violation of the designed model of the chart. The current study evaluates the in-control robustness properties of a chart that is based on the mixture of the statistics of cumulative sum and exponentially weighted moving averages (CS-EWMA) control charts for monitoring the process dispersion under normal, nonnormal, and contaminated normal environments. The in-control robustness performance of the CS-EWMA chart is compared with some existing control charts. Moreover, the appropriate values of the design coefficients for selected charts are also determined. In-control robustness is evaluated in terms of different properties of run length distribution, such as average run length, standard deviation of the run length, and various percentile points. In addition, a real-life application of all the selected charts based on the colonoscopy procedure is considered for practical implementation. It is found that the CS-EWMA chart has a better in-control robustness performance as compared with its counterparts.