Statistical Process Control is regarded as a field that provides statistical instruments to detect changes in processes and monitor data flows. By means of Statistical Process Control, which has a dynamic structure, possible problems are determined by following the process; the factors causing the problem are established and solutions are produced. Quality Control, as the control process applied in the production stages, is a crucial function in order to maximize consumer satisfaction and it is used in all phases of statistical methods; design, production and service activities. The primary goal of quality control is to maintain the rate of defective products at a minimum level. Being one of the most effective tools in quality control, Control Charts are a significant method of statistical process control, which is referred to in the phase of improving the production process. Fundamentally, Control Charts are used to specify the factors that cause variability.
In this study, it is presented by which methods possible deviations from the center line are detected, the structure and types of Control Charts used to improve the process are evaluated; thereby the Quantitative and Qualitative Control Charts are explained theoretically.
Additionally, applications on Quantitative and Qualitative Control Charts are performed and control methods used for control charts are explained and an application for calculating acceptance probabilities are included.