Paper Title:
Cutting Parameter Optimization Technique for High Efficiency NC Machining
  Abstract

High efficient cutting process technique is one of the main development directions of cutting process technology in the future, a reasonable choice of NC machining cutting parameter is an important way to realize high efficiency NC machining. NC machining cutting parameter optimization techniques were studied, using BP neural network, milling parameters optimization model of aluminum alloy shell structure was built, and the structure of BP neural network was analysed, realizing the optimizing of the BP neural network model, the improving of the convergence accuracy, convergence speed, prediction accuracy, generalization ability of BP neural network model, which optimized the cutting parameters selection and predicted the processing efficiency to provide a theoretical basis for the selection of high efficiency NC machining cutting parameter. Production practice showed: the application of the optimized cutting parameters of BP neural network for processing could improve processing efficiency, reduce costs notablely while guaranteeing the processing quality, and achieve the optimization of integrated application efficiency for high efficiency NC machining and NC machine, so it has a higher promotional value.

  Info
Periodical
Advanced Materials Research (Volumes 211-212)
Edited by
Ran Chen
Pages
167-171
DOI
10.4028/www.scientific.net/AMR.211-212.167
Citation
A. J. Cai, S. H. Guo, Z. Y. Dong, H. W. Guo, "Cutting Parameter Optimization Technique for High Efficiency NC Machining", Advanced Materials Research, Vols. 211-212, pp. 167-171, 2011
Online since
February 2011
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Price
$32.00
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