Identification of cutting conditions by using an analytical model and genetic algorithms for micro-end-milling operations Article

cited authors

  • Tansel, IN; Bao, WY; Tansel, B; Shisler, R; Smith, D; Murray, J


  • Identification of cutting conditions simplifies monitoring of machining operations to estimate tool wear and detection of breakage. An analytical model is introduced to simulate micro-end-milling operations more accurately than the conventional models by considering the feed rate. A genetic algorithm-based cutting condition identification program was developed to estimate the entry and exit angles. In all the studied cases, the program estimated the entry and exit angles with less than 3% error in less than 20 generations. In 20 to 150 generations error was reduced to less than 1%. The proposed procedure was found accurate and efficient for on-line monitoring applications.

publication date

  • December 1, 1998

start page

  • 779

end page

  • 784


  • 1998