Evaluation of thrust force and surface roughness in drilling composite maternal using Taguchi analysis and neural network

被引：188

作者：

Tsao, C. C. ^{[1
]}

Hocheng, H. ^{[2
]}

机构：

[1] Ta Hua Inst Technol, Dept Automat Engn, Hsinchu 30740, Taiwan

[2] Natl Tsing Hua Univ, Dept Power Mech Engn, Hsinchu 30013, Taiwan

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 2008年 / 203卷 / 1-3期

关键词：

candle stick drill; drilling; composite material; radial basis function network; thrust force; surface roughness; Taguchi method;

D O I：

10.1016/j.jmatprotec.2006.04.126

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents the prediction and evaluation of thrust force and surface roughness in drilling of composite material using candle stick drill. The approach is based on Taguchi method and the artificial neural network. The experimental results indicate that the feed rate and the drill diameter are the most significant factors affecting the thrust force, while the feed rate and spindle speed contribute the most to the surface roughness. In this study, the objective was to establish a correlation between the feed rate, spindle speed and drill diameter with the induced thrust force and surface roughness in drilling composite laminate. The correlations were obtained by multi-variable regression analysis and radial basis function network (RBFN) and compared with the experimental results. The results indicate the RBFN is more effective than multi-variable regression analysis. (C) 2007 Elsevier B.V. All rights reserved.

引用

页码：342 / 348

页数：7

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