Intelligent support system for monitoring machining processes

Abstract

The intelligent support system for monitoring machining processes was objective of our research. The paper presents process of development of this system which can used in real enterprises. Methodology: to create of the system we use methods of artificial intelligence (neural networks, decision trees and rules, fuzzy logic), using AI methods we created procedures support monitoring machining processes: diagnosis of machining process disturbances using decision rules, control of stability of the machining process based on control card analysis using neural networks, control of surface roughness parameter using neural networks and decision trees and monitoring machine tool through control and compensation of thermal deformations of ball screws of CNC machine tools using neural networks. To optimize of AI models we compared many the models with different structures, chose the best models and used them in intelligent system.