Quality cost control model based on fuzzy neural network

Abstract

In order to develop a new quality cost control model, the paper first sets the third level subject of quality cost base on the PAF model, which is that quality cost is composed of prevention cost, appraisal cost, failure cost and does Pareto analysis according to the history data, finding the main influential subjects, second, it uses correlation analysis and partial correlation analysis to find the actual influential subjects, then it analyses the controllable factors and uncontrollable factors to these actual influential subjects. Finally, based on all the analysis results, and by taking use of fuzzy control and neural network, the paper sets fuzzy subsets and rules and establishes a quality cost control model based on them to facilitate automatic quality cost control.