Genetic algorithms for automatic design of fuzzy decision systems for intelligent manufacturing

摘要

Artificial neural networks (ANNs) have been successfully applied in different fields of manufacturing. Monitoring and modelling of manufacturing processes obviously belong to the most promising areas, where real-time nature, uncertainty handling and learning abilities are essential. However, mainly because of the "black box" nature of ANNs, these solutions have limited industrial acceptance. In the paper, a combined use of the neural and fuzzy techniques in cutting tool monitoring is illustrated. We introduce a genetic algorithm based approach to overcome problems, including rule selection and redundancy checking. Finally the results are compared with ANN and previous neuro-fuzzy (NF) approaches.