Estimating the quality of process yield by fuzzy sets and systems

Fuzzy grading is a multi-class problem, and is used for grading the product according to the degree of fitness for use, customer acceptance or commercial value. In this respect, the production system requires intelligent adjustments. Fuzzy set theory has a variety of applications in different fields. The most fruitful applications are in the field of modeling and control of production systems. Fuzzy logic may be used to control the key quality parameters, grade product quality to reduce the variations and adjust to the specification limits. grading expresses the quality level of product by membership degrees in which belonging or not-belonging to a quality set is gradual. Similarly, the quality control charts are also focused on the reduction of variability and grading the key quality characteristics. The control limits are used to establish the natural spread or range of process so the controller will not signal changes in the process until the natural limits are exceeded. However, there is a logical inconsistency in control chart approaches, due to their crisp grading nature which are expressed as either conforming (good) or nonconforming (poor) to specifications. In this study, a new fuzzy grading approach was developed based on a fuzzy expert system. The outcomes of the fuzzy grading system were clearly proven to be more vigorous and flexible than the crisp control methods.