The collection of data in the process can be done much faster and easier as a result of industrial automation allowing large amount of data for analysis. Because production processes are directed in part by inertial elements, if the data is collected at a higher rate, the observations will be auto-correlated. The violation of the data independence assumption causes an increasing in the false alarms rate and the quality costs of the traditional process monitoring tools. To mitigate this problem, we propose an economic-statistical design of a variable parameters control chart, also known as fully adaptive. The results show the effectiveness of this approach for the statistical monitoring of these processes. The “fully adaptive control charts” have been fairly evaluated in these scenarios, and are proposed as an important tool for the process monitoring under this circumstances.