Statistical Process Control (SPC) and Automatic Process Control (APC) bare based on different strategies for process quality improvement and process adjustment. SPC is often used to monitor long-term process quality and removing causes of process disturbance by the implementation of appropriate control charts and it is effective in detecting changes due to special causes. On the other hand, APC is used to compensate for short- term variations due to the common causes and attempts to continuously adjust the process level close to the target or set points. It uses different controllers with different properties. APC controllers are more tactical in nature with a primary focus on continuous adjustments of the process. The integration of SPC and APC started first in 1988 by J. MacGregor who introduced this concept into the research community. Since then, the research in integrating these methods came up to a conclusion that combination of these two techniques will result in better performance than using each alone. Different techniques are proposed in the literature to integrate SPC and APC, based on different criteria. Many researchers have studied economic cost models to develop the economic design of SPC only. Models for the economic design of the integration of SPC and APC have been limited but it has gained significant interest in recent years. In this paper we will highlight first on the available methods that propose the integration of these two techniques. Then the economic design methods available in the literature will be summarized and reported. Comparison between different methodologies, stating the pros and cons will be stated. Based on this study, we propose some extensions regarding economic cost models, quality cost, and related topics.