TY - GEN
T1 - Automatic selection of cutting tools geometry using an evolutionary approach
AU - Duran, Orlando
AU - Rodriguez, Nibaldo
AU - Consalter, Luiz Airton
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Evolutionary Computation
KW - Machining
KW - Tool Geometry Optimization
UR - http://www.scopus.com/inward/record.url?scp=48249145379&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-69052-8_59
DO - 10.1007/978-3-540-69052-8_59
M3 - Conference contribution
AN - SCOPUS:48249145379
SN - 354069045X
SN - 9783540690450
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 561
EP - 569
BT - New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
T2 - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
Y2 - 18 June 2008 through 20 June 2008
ER -