Intelligent Modeling and Decision Making for Product Quality of Manufacturing System Based on Fuzzy Cognitive Map

Recent research finds that consumers pay more and more attention to the high grade product. An intelligent decision making system is proposed in this paper, the purpose of which is to monitor product quality of manufacturing system and give warnings to the quality managers accordingly. Since the complex interaction among the multivariate quality characteristic (QC) and the intelligent model is hard to be manually managed, the well-performing machine learning algorithms need to be proposed to support an automatic control of product quality. And many decision making tools have been developed to monitor product quality with the intelligent control model. Fuzzy cognitive map (FCM) is a popular tool for intelligent modeling, and is usually applied to many fields. In this paper, FCM is used for intelligent modeling in the decision making process of manufacturing system. Based on the mechanism, we design an intelligent model to solve the decision making problem of product quality control. Then, the effect of varying the support scale of trained data is tested by using FCM in different environments. Finally, we get some useful conclusions and discuss several potential research developments in the future.