This paper presents, a control methodology based on experimental data of the tool wear as a function of cutting variables. In automatic machine tools there is strong need to control the tool wear by adjustment of the cutting parameters. In this connection, a control system, which can adjust the cutting parameters for a desired wear rate, is necessary. A regression relation is also established between the flank-wear and the cutting parameters. An inversely trained neural network model, which supplies the modified values of the cutting parameters, is used as a controller. The results are shown in the form of tables and graphs.

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