Paper Title:
Optimization of Cutting Conditions in Ultra-Precision Turning Based on Mixed Genetic-Simulated Annealing Algorithm
  Abstract

In ultra-precision turning process, the predictive modeling of surface roughness and the optimization of cutting conditions are the key factors to improve the quality of products and raise the efficiency of equipments. In this paper, the application of genetic algorithm in identifying nonlinear surface roughness prediction model is discussed, and presents mixed genetic-simulated annealing algorithm approach to optimization of cutting conditions in ultra-precision turning. The experiment was carried out with diamond cutting tools, for machining single crystal aluminum optics covering a wide range of machining conditions. The results of fitting of prediction model and optimal cutting conditions using genetic algorithm (GA) are compared with least square method and traditional optimal method.

  Info
Periodical
Key Engineering Materials (Volumes 315-316)
Edited by
Zhejun Yuan, Xipeng Xu, Dunwen Zuo, Julong Yuan and Yingxue Yao
Pages
617-622
DOI
10.4028/www.scientific.net/KEM.315-316.617
Citation
Z. S. Lu, M. H. Wang, "Optimization of Cutting Conditions in Ultra-Precision Turning Based on Mixed Genetic-Simulated Annealing Algorithm ", Key Engineering Materials, Vols. 315-316, pp. 617-622, 2006
Online since
July 2006
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$32.00
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