Introduction.

In the last decade High-Speed Machining has been of special interest to the academic and industrial sectors. Its influence on the performance of machining by chip removal allows a high value of removed metal and a good surface finish. Goals. This work shows the determination of technological indicators and cutting parameters in High-Speed Machining in steels with the combined use of experimental methods, numerical simulation and Artificial Intelligence.

Methods.

Experimental tests were carried out in High-Speed Machining of various types of steels, using various cutting tools and processing conditions. Mathematical statistical methods were used for correlation analyzes, experimental conditions were simulated by the Finite Elements Method and through Artificial Intelligence tools, combined predictive models were obtained.

Results.

New criteria were defined for the study of the machinability of steels that allow evaluating their performance; mathematical correlation models were obtained between the fundamental variables of High-Speed Machining of steels by experimental methods; numerical models were obtained by Finite Element Analysis that complement the experimental tests; the prediction of technological indicators was defined and implemented using Artificial Intelligence tools.

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