MODELLING OF THE TEMPERATURE IN THE CHIP-FORMING ZONE USING ARTIFICIAL INTELLIGENCE TECHNIQUES
Heat generation in the cutting zone occurs as a result of the work done in metal cutting. In this study, in order to measure the temperature generated in the chip-forming zone, numerous experiments were carried out for different cutting regimes. During these experiments, the chip's top temperature was measured using an infrared camera. Collected data were analyzed, and temperature dependence on various cutting regimes was formulated. After that, measured data were modelled using the various techniques: response surface methodology, various types of artificial neural networks and neuro-fuzzy system. The accuracy of the proposed models is presented as well as their suitability for the considered problem. Finally, the system for the adaptive control of the cutting temperature, based on the proposed models, is presented.
metal cutting artificial neural networks cutting temperature neuro-fuzzy model