Prediction of cutting forces in helical end milling fiber reinforced polymers

被引:158
|
作者
Kalla, Devi [1 ]
Sheikh-Ahmad, Jamal [2 ]
Twomey, Janet [1 ]
机构
[1] Wichita State Univ, Dept Ind & Mfg Engn, Wichita, KS 67260 USA
[2] Petr Inst, Mech Engn Program, Abu Dhabi, U Arab Emirates
基金
美国国家科学基金会;
关键词
Helical end mill; Specific cutting energy; FRP; Committee neural network; Fiber orientation; NEURAL-NETWORK MODEL; MULTIPLE-REGRESSION; COMPOSITES; DELAMINATION; SIMULATION;
D O I
10.1016/j.ijmachtools.2010.06.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Machining of fiber reinforced composites is an important activity in the integration of these advanced materials into engineering applications. Machining damage due to excessive cutting forces may result in rejecting the composite components at the last stages of their production cycle. Therefore, the ability to predict the cutting forces is essential for selecting process parameters that would result in minimum machining damage. This work utilizes mechanistic modeling techniques for simulating the cutting of carbon fiber-reinforced polymers (CFRP) with a helical end mill. A methodology is developed for predicting the cutting forces by transforming specific cutting energies from orthogonal cutting to oblique cutting. It is shown that the method developed is capable of predicting the cutting forces in helical end milling of unidirectional and multidirectional composites and over the entire range of fiber orientations from 0 degrees to 180 degrees. This is a significant improvement over previous models that were only capable of addressing orthogonal cutting and/or a limited range of fiber orientations. Model predictions were compared with experimental data and were found to be in good agreement in cutting unidirectional laminate, but with lesser agreement in the case of a multidirectional laminate. Published by Elsevier Ltd.
引用
收藏
页码:882 / 891
页数:10
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