The Sustainability Of Neural Network Applications Within Finite Element Analysis In Sheet Metal Forming: A Review

Jamli, Mohamad Ridzuan and Che Zainal Abidin, Nik Mohd Farid (2019) The Sustainability Of Neural Network Applications Within Finite Element Analysis In Sheet Metal Forming: A Review. Measurement: Journal of the International Measurement Confederation, 138. pp. 446-460. ISSN 0263-2241

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Abstract

The prediction of springback in sheet metal is vital to ensure economical metal forming. The latest nonlinear recovery in finite element analysis is used to achieve accurate results, but this method has become more complicated and requires complex computational programming to develop a constitutive model. Having the potential to assist the complexity, computational intelligence approach is often regarded as a statistical method that does not contribute to the development of a constitutive model. To provide a reference for researchers who are studying the potential application of computational intelligence in springback research, a review of studies into the development of sheet metal forming and the application of neural network to predict springback is presented in this research paper. It can be summarized as: (1) Springback is influenced by various factors that are involved in the sheet metal forming process. (2) The main complexity in FE analysis is the development of a constitutive model of a material that has the potential to be solved by using the computational intelligence approach. (3) The existing neural network approach for solving springback predictions is unable to represent all the factors that affect the results ofthe analysis

Item Type:	Article
Uncontrolled Keywords:	Neural network, Finite element, Springback, Sheet metal forming
Divisions:	Faculty of Manufacturing Engineering > Department of Manufacturing Process
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	22 Dec 2020 12:48
Last Modified:	12 Jul 2021 12:13
URI:	http://eprints.utem.edu.my/id/eprint/24444
Statistic Details:	View Download Statistic

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