A Checking Procedure for Input Data of Attribute Control Charts Under Uncertainty: The Cases of Normality

Control charts are one of the most important tools of statistical quality control, used to identify whether something is wrong in a manufacturing process or not. Although the assumption of normality is often overlooked in real world problems, checking the normality condition is an important component of the process, as the inferences made based on quality control charts rely on the assumption of normality. On the other hand, control charts are mostly designed according to the logic of measuring certain qualities based on certain data, a considerable number of uncertainties and linguistic differences are encountered by practitioners in the inspection process. From this point of view, in this study, the stage of normality testing of the evaluations obtained in the form of intuitionistic fuzzy numbers is examined. A numerical example is also performed to illustrate implementation steps of the proposed approach.