Trends on Process Capability Indices in Fuzzy Environment

After the fuzzy set theory was introduced and developed, many studies have been realized to combine quality control methods and fuzzy set theory. This chapter is including the categorization of most essential works on fuzzy process capability indices in the following four main categories: (1) Lee et al.’s method and its extensions: This class deals with the method of modeling and estimating the membership function of process capability indices where all data and specifications are fuzzy numbers; (2) Parchami et al.’s method and its extensions: This class deals with the problem of obtaining fuzzy process capability indices based on fuzzy specification limits and crisp data by extension principle approach; (3) Kaya and Kahraman’s method and its extensions: This class deals with the problem of estimating the classical process capability indices by a triangular shaped fuzzy number when both specifications and data are crisp; (4) Yongting’s method and its extensions: This class deals with introducing process capability indices based on fuzzy quality where the data and parameters are crisp. After presenting the basic idea of the main works, all related studies briefly reviewed in each class. Some numerical examples are presented to show the applicability of the proposed methods.