Control charts are primary tools for statistical control of process that can be designed with simple methods such as Shewhart control chart or other statistical criteria or economical criteria. Economic design of control charts involves the determination of the sample size (n), the time interval between samples (h), and the coefficient of the control limits (k).

Most of the designed models for the control charts are used to maintain the current levels of the process quality. Weheba (1996) developed a proactive model that can be used to process improvement. However, this model involved the economic design of single control charts (x bar or S). In practice, two charts are employed to monitor the process one for monitoring changes in mean of process and the other for monitoring changes in dispersion of process. Therefore, we first consider Weheba’s proactive model and then we study it’s extension that extended by Epprecht (2007). Epprecht proactive model (2007) is in relation to joint process average and dispersion control chart monitoring. Finally we consider the obtained model optimization. Optimization indicates locating the optimum control chart design parameters that minimize the Net Present Cost (NPC) per unit time. Then this optimization and Epprecht proactive model application is illustrated through an example.