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Journal of Intelligent Manufacturing

, Volume 16, Issue 1, pp 93–102 | Cite as

Milling force prediction using regression and neural networks

  • T. RadhakrishnanEmail author
  • Uday Nandan
Article

Abstract

This study focuses on developing a good empirical relationship between the cutting force in an end milling operation and the cutting parameters such as speed, feed and depth-of-cut, by using both multiple regression and neural network modeling processes. A regression model was first fitted to experimentally collected data and any abnormal data points indicated by this analysis were filtered out. By repeating this process several times, a final set of filtered data was obtained and analyzed using neural networks to yield a good, final model. This study shows that analyzing milling force data using conventional regression can lead to a more accurate neural networks model for force prediction.

Keywords

Milling force model cutting parameters multiple regression neural networks 

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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Mechanical Engineering DepartmentVillanova UniversityVillanova, PA
  2. 2.Tyco InternationalMorristown

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