Statistical process control is based on comparing data collected by calculating control limits. In that way, conclusions are reached about the process itself and the possible need for improvement and eventual removal of certain anomalies in the process. This indicates how statistical process and quality control ensures the quality of products that will be in line with the basic requirements and needs of users. The key to conducting a product quality assessment is primarily data collection, processing, and finally analysis. Control charts enable better product quality results to be achieved. The analysis of control charts for measuring (numerical) and descriptive (attributive) properties showed the need to determine first the type of data being processed, as far as attributive or measurable data are concerned. In the first case, the types of errors are determined, and in the second the number of samples. The main idea is to find an appropriate and satisfactory level in the quality process by identifying all possible errors through a control chart if there are and assess which elements and stages of the process need more attention in order to improve it. The production of the control map is based on statistics, and the best way to present a control chart is to use a graphical diagram. The results of the research showed that control charts are a very powerful tool for early detection of errors that occurred in a process.