Paper Title:
Optimized Machining Condition Selection for High-Quality Surface in High-Speed Finish Milling of Molds
  Abstract

Today, the trend in die and mold manufacturing is to pursue high-quality surface topology using high-speed finish milling operation. This paper presents a new approach to optimize machining conditions according to the required material removal rate (MRR), focusing on obtaining a high-quality surface. In this approach, the prediction model of surface roughness using the 2-staged artificial neural network (ANN) is employed for the objective function. Furthermore, an additional surface quality criterion is also used for the optimization problem using the genetic algorithm. It has been investigated that optimized machining conditions can be selected to obtain the high-quality surface within allowable reliability while maintaining a high-quality surface, under the given desired MRR.

  Info
Periodical
Edited by
Dongming Guo, Tsunemoto Kuriyagawa, Jun Wang and Jun’ichi Tamaki
Pages
711-718
DOI
10.4028/www.scientific.net/KEM.329.711
Citation
S. W. Lee, S.H. Nam, H. J. Choi, E.G. Kang, K.Y. Ryu, "Optimized Machining Condition Selection for High-Quality Surface in High-Speed Finish Milling of Molds", Key Engineering Materials, Vol. 329, pp. 711-718, 2007
Online since
January 2007
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