Automatic selection of cutting tools geometry using an evolutionary approach

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper presents the application of an evolutionary algorithm for the definition of the optimal cutting tool geometry in machining operations. In essence, the proposed approach points to the use of a genetic algorithm for selecting adequate cutting tool angles. This optimization approach was developed considering a Macro Optimization Model reported in the literature. To determine the most appropriate configuration of the genetic algorithm and its parameters a set of tests were carried out. The different algorithm settings were tested against data obtained from experimental test carried out and provided by the authors of the optimization model. A variety of simulations were carried out to validate the performance of the system and to show the usefulness of the applied approach. The definition of proposed approach also has presented the following main conclusion: through the utilization of the evolutionary approach, the selection of the appropriate cutting tool geometry is possible in real world environments.

Original languageEnglish
Title of host publicationNew Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
Pages561-569
Number of pages9
DOIs
StatePublished - 4 Aug 2008
Event21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 - Wroclaw, Poland
Duration: 18 Jun 200820 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5027 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
CountryPoland
CityWroclaw
Period18/06/0820/06/08

Keywords

  • Evolutionary Computation
  • Machining
  • Tool Geometry Optimization

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