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Proceedings Paper

CN force predication model in milling of carbon fiber reinforced polymers
Author(s): Devi Kalla; Prashant Lodhia; Bijay Bajracharya; Janet Twomey; Jamal Sheikh-Ahmad
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Paper Abstract

Fiber reinforced polymers are widely used in the transportation, aerospace and chemical industries. In rare instances these materials are produced net-shape, and secondary processing such as machining and assembly may be required to produce a finished product. Because fiber reinforced polymers are heterogeneous materials, they do not machine in a similar way to metals. Thus, the theory of metal machining is not valid for the analysis of machining of fiber- reinforced composites. Previous attempts in modeling this problem have adopted Merchant's theory from metal cutting by assuming that chip formation takes place in a shear plane which inclination angle is determined by the minimum energy principle. This class of models showed that model predictions are valid only for fiber orientations less than 60°. The work presented here focuses on providing predictive models for the cutting forces in unidirectional composites. The models are based on the specific cutting energy principle and account for a wide range of fiber orientations and chip thickness. Results from two forms of non-linear modeling methods, non-linear regression and committee neural networks, were compared. It was found that committee neural networks provide better prediction capability by smoothing and capturing the inherent non-linearity in the data. The model predictions were found to be in good agreement with experimental results over the entire range of fiber orientations from 0 to 180°.

Paper Details

Date Published: 16 November 2005
PDF: 12 pages
Proc. SPIE 5999, Intelligent Systems in Design and Manufacturing VI, 59990S (16 November 2005); doi: 10.1117/12.632100
Show Author Affiliations
Devi Kalla, Wichita State Univ. (United States)
Prashant Lodhia, Wichita State Univ. (United States)
Bijay Bajracharya, Wichita State Univ. (United States)
Janet Twomey, Wichita State Univ. (United States)
Jamal Sheikh-Ahmad, Wichita State Univ. (United States)

Published in SPIE Proceedings Vol. 5999:
Intelligent Systems in Design and Manufacturing VI
Bhaskaran Gopalakrishnan, Editor(s)

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