Cutting Parameter Optimization for Multi-Pass Milling Operations by Genetic Algorithms

Abstract:

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Parameter optimization in multi-pass cutting operations involves optimal selection of cutting speed, feed rate, depth of cut, and the number of passes, duo to significant influence of these parameters on the quality of machined parts and machining economics. In this paper, a non-linear mathematical model based on minimum production cost for multi-pass milling operations is presented. The unwanted material is removed by one finishing pass and one or multiple roughing passes depending on the total depth of cut. Various realistic constraints are considered when developing the model. Optimal values of machining parameters are found by Genetic Algorithms. An example is presented to illustrate the optimization model and solution approach. The method yields lower unit production costs compared with the results from the literature and machining data handbook.

Info:

Periodical:

Advanced Materials Research (Volumes 160-162)

Edited by:

Guojun Zhang and Jessica Xu

Pages:

1738-1743

DOI:

10.4028/www.scientific.net/AMR.160-162.1738

Citation:

L. B. An et al., "Cutting Parameter Optimization for Multi-Pass Milling Operations by Genetic Algorithms", Advanced Materials Research, Vols. 160-162, pp. 1738-1743, 2011

Online since:

November 2010

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Price:

$35.00

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