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Particle Swarm Optimization for Milling Titanium Alloy

Published online by Cambridge University Press:  14 February 2012

I. Escamilla ,
L. Torres ,
B. Gonzalez  and
P. Zambrano
I. Escamilla
Affiliation:
Facultad de Ingeniería Mecánica y Eléctrica. Ave. Universidad s/n. San Nicolás de los Garza, N. [email protected]
L. Torres
Affiliation:
Facultad de Ingeniería Mecánica y Eléctrica. Ave. Universidad s/n. San Nicolás de los Garza, N. [email protected]
B. Gonzalez
Affiliation:
Facultad de Ingeniería Mecánica y Eléctrica. Ave. Universidad s/n. San Nicolás de los Garza, N. [email protected]
P. Zambrano
Affiliation:
Facultad de Ingeniería Mecánica y Eléctrica. Ave. Universidad s/n. San Nicolás de los Garza, N. [email protected]
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Abstract

Optimum machining parameters are of great concern in manufacturing environments, where economy of machining operation plays a key role in competitiveness in the market. Many researchers have dealt with the optimization of machining parameters for milling operations. In this paper, optimization procedures based on particle swarm optimization algorithm are developed for find machining parameters in milling operation. It describes development and utilization of the methodology that determines optimum Pareto’s front analyzing feed, speed and depth for milling operation. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and a swarm intelligent neural network system. Results show that particle swarm optimization is an effective method for solving multi-objective optimization problems, and also, that an integrated system of neural networks and swarm intelligence can be used to solve complex machining optimization problems.

Keywords

Multi-objective optimizationparticle swarm optimizationmachining parametersTitanium Alloy
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1373: Symposium S4 – Advanced Structural Materials—2011 , 2012 , imrc-1373-s4-26
Copyright
Copyright © Materials Research Society 2012

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References

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