Manufacturing Technology Today

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Tool Wear Monitoring and Control


Affiliations
1 Department of Industrial and Production Engg., K.L. College of Engineering, Vaddeswaram, Guntur (Dist.), India
2 Department of the Mechanical Engineering, Chaitanya Engineering College, Visakhapatnam, India
     

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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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  • Tool Wear Monitoring and Control

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Authors

K. Rama Kotaiah
Department of Industrial and Production Engg., K.L. College of Engineering, Vaddeswaram, Guntur (Dist.), India
J. Srinivas
Department of the Mechanical Engineering, Chaitanya Engineering College, Visakhapatnam, India
K. Jayanendra Babu
Department of Industrial and Production Engg., K.L. College of Engineering, Vaddeswaram, Guntur (Dist.), India

Abstract


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.