Integration of feedforward neural network and finite element in the draw-bend springback prediction

Jamli, Mohamad Ridzuan and Mohd Ihsan, Ahmad Kamal Ariffin and Abdul Wahab, Dzuraidah (2013) Integration of feedforward neural network and finite element in the draw-bend springback prediction. Expert Systems with Applications, 41. pp. 3662-3670. ISSN 0957-4174

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Abstract

To achieve accurate results, current nonlinear elastic recovery applications of finite element (FE) analysis have become more complicated for sheet metal springback prediction. In this paper, an alternative modelling method able to facilitate nonlinear recovery was developed for springback prediction. The nonlinear elastic recovery was processed using back-propagation networks in an artificial neural network (ANN). This approach is able to perform pattern recognition and create direct mapping of the elasticallydriven change after plastic deformation. The FE program for the sheet metal springback experiment was carried out with the integration of ANN. The results obtained at the end of the FE analyses were found to have improved in comparison to the measured data.

Item Type:	Article
Uncontrolled Keywords:	Finite element, Neural network, Nonlinear elastic recovery, Springback prediction
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Manufacturing Engineering > Department of Manufacturing Process
Depositing User:	Mohamad Ridzuan Jamli
Date Deposited:	02 Jan 2017 03:57
Last Modified:	18 Jul 2021 17:16
URI:	http://eprints.utem.edu.my/id/eprint/17851
Statistic Details:	View Download Statistic

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