Modélisation Des Phénomènes Thermomécaniques À L’interface Outil-pièce À L'aide De L’intelligence Artificielle En Fraisage

Résumé: he increase in cutting temperature presents one of the important aspects during milling operations, because it directly influences the residual stresses, the dimensions of the machined parts and the life of the cutting tools. The cutting parameters, the material and the geometric shape of the tool are the important factors that affect the cutting temperature. In our study, an intelligent infrared camera is used to measure the temperature in the cutting area as a function of time. The objective is the prediction of the effects of the cutting parameters on the temperature at the tool-part interface during the milling operation of AISI 1060 steel with carbide tools; A comparison between two experimental methods and artificial intelligence was made. The results showed that the cutting temperature increases when the values of depth of cut, cutting speed, and cutting time increase; the remaining feed per tooth is less influenced except for the maximum cutting speed values. The predicted values, with this fuzzy model, are in good agreement with the experimental values, with an average error percentage of 2.242%, which corresponds to an accuracy of 97.757%, The fuzzy modeling technique could be an effective and economical method for the prediction of cutting temperature during milling operations

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