Fuzzy inference system for modelling cutting temperature of AISI 1060 Steel in turning operations

During the cutting, knowledge of thermal phenomena induced is essential for the understanding of the cut and to improve the machinability of certain materials. Moreover, these temperature influence the final product (residual stresses, surface states, geometrical tolerances, etc.) Experimental techniques were used to measure the cutting temperature during machining: indirect measurements, direct measurements, optical temperature measurement, and analytical and numerical methods. Experimental techniques are enormously difficult and require a lot of time and material. They allowed choosing in a way not precise the parameters of cut. Thus some works have used soft computing techniques to find solutions for the selection of cutting conditions problems, because of their efficiency in modelling the different thermo-mechanical phenomena of cutting. However, the results obtained from these techniques are sometimes uncertain, imprecise and approximate. To avoid these disadvantages, and in order to improve the selection procedure of cutting parameters and to study their effects on the cutting temperature of the AISI 1060 steel, we propose to solve this problem with fuzzy logic. (paper)