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Tool-Wear Monitoring and Control

[+] Author Affiliations
J. Srinivas

Chaitanya Engineering College

Rao Dukkipati

Fairfield University

V. Sreebalaji

SCSVMV Deemed University

K. Ramakotaih

K.L. College of Engineering

Paper No. IMECE2005-80799, pp. 901-904; 4 pages
doi:10.1115/IMECE2005-80799
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Manufacturing Engineering and Materials Handling, Parts A and B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Manufacturing Engineering Division and Materials Handling Division
  • ISBN: 0-7918-4223-1 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

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.

Copyright © 2005 by ASME
Topics: Wear

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