Paper Title:
Cutting Parameter Optimization for Multi-Pass Milling Operations by Genetic Algorithms
  Abstract

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, L. J. Feng, C. G. Lu, "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
$32.00
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