Abstarct: Control charts are one of the seven tools for controlling the statistical process. The purpose of this dissertation is to explain the concept of the control graph in a fuzzy environment. Control charts in the classical environment were first introduced in 1920 by Shewhart . Classical control charts include two limited states of zero and one that do not provide the user with complete and proper information about the production process. For this reason, using fuzzy quality, generalized descxriptive quality control charts, such as the defective component ratio diagram , the number of defective items, and the number of defects per inspection unit and the average number of defects in the fuzzy environment. Fuzzy quality is used to generalize the number of defective items in the fuzzy state. It is appropriate to use fuzzy control charts in cases where the defective quality of the defective items is not equal to the user. The results and answers of this generalization by using criteria such as the characteristic curve of performance and ARL . At the time of the creation of the change in the mean or the variance of the process, it is compared with the standard quality control.