Interval type-2 fuzzy c-Control charts using ranking methods

Abstract

Control charts are important for process or product because they provide information about the control situation of process and product. Because of this feature, control charts are used in many fields. Information about the product and/or process, which is under control or not, can be provided by looking the control charts. Fuzzy numbers are used to reduce information losses in operations with crisp numbers. In control charts applications, especially for qualitative control charts, the fuzzy set theory reduces the information losses and provide more flexible decision-making process. In the literature, there are some fuzzy control charts with type-1 fuzzy sets but there are few studies about fuzzy control charts regarding the cases where the data are expressed by type-2 fuzzy sets. The purpose of the study is to create an innovation using the ranking methods, which has not used for control charts in accessible literature, for the fuzzy control charts with interval type-2 fuzzy sets. The fuzzy results are compared with the crisp results. This study introduces ranking methods as new approach to generate interval type-2 fuzzy control charts, which is a different field.

Keywords

• Interval type-2 trapezoidal fuzzy sets,Fuzzy control charts,c-Control charts,Nonconformities,Ranking methods

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