Simulation of Direct Extrusion Process and Optimal Design of Technological Parameters Using FEM and Artificial Neural Network

Abstract:

Article Preview

This study aims the modeling and simulation of the direct extrusion process and determination of optimal process parameters using Finite Element Method (FEM) and Artificial Neural Network (ANN) cooperatively. First, the die set has been designed for direct extrusion of an aluminum rod and its numerical simulation has been prepared by mean of ABAQUS/EXPLITIC finite element code. So, both the values of the process parameters according to extrusion load and the critical stress values have been determined. After, the ANN model of the process has been developed under MATLAB and has been trained with the results of finite element simulations. Also, the optimization software which can run together the ANN model has been developed and has been used to determine the optimum process parameters.

Info:

Periodical:

Edited by:

Luca Tomesani and Lorenzo Donati

Pages:

185-192

Citation:

D. Karayel, "Simulation of Direct Extrusion Process and Optimal Design of Technological Parameters Using FEM and Artificial Neural Network", Key Engineering Materials, Vol. 367, pp. 185-192, 2008

Online since:

February 2008

Authors:

Export:

Price:

$38.00

[1] F. H. Raj, R.S. Sharma, S. Srivastava, C. Patvardhan, Modeling of Manufacturing Process with ANNs for Intelligent Manufacturing, International Journal of Machine Tools & Manufacturing vol. 40 (2000) pp.851-868.

DOI: https://doi.org/10.1016/s0890-6955(99)00094-2

[2] H. -S. Lin, C. -Y. Lee, C. -H. Wu, Hole Flanging with Cold Extrusion on Sheet Metals by FE Simulation, International Journal of Machine Tools & Manufacturing vol. 47 (2007) pp.168-174.

DOI: https://doi.org/10.1016/j.ijmachtools.2006.02.002

[3] H.J. Li, L.H. Qi, H.M. Han, L.J. Guo, Neural Network Modeling and Optimization of SemiSolid Extrusion for Aluminum Matrix Composites, Journal of Materials Processing Technology vol. 151 (2004) pp.126-132.

DOI: https://doi.org/10.1016/j.jmatprotec.2004.04.027

[4] M. Kleiner, M. Schikorra, Simulation of Welding Chamber Conditions for Composite Profile Extrusion, Journal of Materials Processing Technology vol. 177 (2006) pp.587-590.

DOI: https://doi.org/10.1016/j.jmatprotec.2006.03.220

[5] B.R. Tibbetts, J.T. -Y. Wen, Extrusion Process Control: Modelling, Identification, and Optimization, IEEE Transactions on Control System Technology vol. 6 (1998) pp.134-145.

[6] B.P.P.A. Gouveia, J.M.C. Rodrigues, N. Bay, P.A.F. Martins, Finite - Element Modeling of Cold Forward Extrusion, Journal of Materials Processing Technology vol. 94 (1999) pp.85-93.

DOI: https://doi.org/10.1016/s0924-0136(99)00084-9

[7] K.D. Hur, Y. Choi, H.T. Yeo, A Design Method for Cold Beckward Extrusion Using FE Analysis, Finite Elements in Analysis and Design vol. 40 (2003) 173-185.

DOI: https://doi.org/10.1016/s0168-874x(02)00222-6

[8] X.Q. Zhang, Y.H. Peng, X.Y. Ruan, K. Yamazaki, Feature Based Integrated Intelligent Sequence Design for Cold Extrusion, Journal of Materials Processing Technology vol. 174 (2006) pp.74-81.

DOI: https://doi.org/10.1016/j.jmatprotec.2004.12.011

[9] A.V. Nagasekhar, Y. Tick-Hon, Optimal Tool Angles for Channel Angular Extrusion of Strain Hardening Materials by Finite Element Analysis, Computational Materials Science vol. 30 (2004) pp.489-495.

DOI: https://doi.org/10.1016/j.commatsci.2004.02.041