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Prediction of burr formation during face milling using a hybrid GMDH network model with optimized cutting conditions

Onwubolu, Godfrey C. (2010) Prediction of burr formation during face milling using a hybrid GMDH network model with optimized cutting conditions. International Journal of Advanced Manufacturing Technology, 44 (11-12). pp. 1083-1093. ISSN 0268-3768

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Abstract

In this paper, a combined hybrid group method for data handling and optimization approach is introduced to predict burr types formed during face milling. The hybrid group method for data handling (hybrid GMDH) network was constructed for realizing predictive models for the machining of aluminum alloy, and differential evolution was selected for the optimization of burr formation problem resulting in finding optimal parameter for minimizing burr formation. Burr type was included as a parameter resulting in a classification scheme in which the burr type becomes the group label and it is therefore possible in the future to classify a machining process into any of these burr types. The resulting hybrid GMDH output was in agreement with experimental results, thereby validating the proposed scheme for modeling and prediction of burr formation in milling operations.

Item Type: Journal Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Ms Mereoni Camailakeba
Date Deposited: 29 Nov 2010 15:58
Last Modified: 16 Jul 2012 20:51
URI: http://repository.usp.ac.fj/id/eprint/1907
UNSPECIFIED

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