Évf. 8 szám 1 (2023)

Gépészeti és járműmérnöki tudományok

Numerical Modelling and Simulation of Sheet Metal Forming Process

Megjelent:

2023-04-30

https://doi.org/10.21791/IJEMS.2023.1.1.

Szerzők

Habbachi Marwen,

University of Miskolc, Institute of Applied Mechanics

Baksa Attila

University of Miskolc, Institute of Applied Mechanics

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Kulcsszavak

Modelling and Simulation Friction effect Mesh Optimization Sheet metal forming Stainless steel

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Copyright (c) 2023 by the authors

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Kiválasztott formátum: APA

Habbachi, M., & Baksa, A. (2023). Numerical Modelling and Simulation of Sheet Metal Forming Process. International Journal of Engineering and Management Sciences, 8(1), 1-6. https://doi.org/10.21791/IJEMS.2023.1.1.

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Beküldött 2023-01-23
Elfogadott 2023-02-04
Publikált 2023-04-30

Absztrakt

Simulation and modelling of sheet metal forming process are well common today in different industries (automotive, aerospace) and several research centers regarding its huge impact for both on production and reliability of the lifecycle of the equipment, and the quality of the product. However, to obtain the best configuration possible with the inputs parameters to achieve high level of production and increasing the durability of the tools needs some extra methods for the optimization for this problem using mostly finite element method cooperated with iterative algorithms based on Artificial Neural Network (ANN) [1]. Whereas this research is focused on modelling of stamping process of stainless steel AISI 304 to investigate to formability of the material, and studying the influence of the friction factor on the quality of the product as well the energy required for each set configuration.

Hivatkozások

1. M. Merklein, J. M. Allwood, B.-A. Behrens, A., Brosius, H. Hagenah, K. Kuzman, K. Mori, A.E. Tekkaya, A. Weckenmann, Bulk forming of sheet metal, Annals of the CIRP 61, 2, pp. 725–745 (2012).
2. Wenqiong Zhang and Dongwei Wang, Optimization of Sheet Metal Forming Process. Parameters by Artificial Neural Network and Orthogonal Test Method, International Conference on Electrical, Mechanical and Industrial Engineering (ICEMIE 2016).
3. Research and development center of science and technology products. The neural network theory and MATLAB7 realize [M]. Beijing: electronic industry press, 2005.
4. Mohamed Azaouzi. Modélisation et Optimisation numérique de l’emboutissage de pièces de précision en tôlerie fine. Modélisation et simulation. Institut National Polytechnique de Lorraine - INPL, 2007.
5. Abaqus Software: http://130.149.89.49:2080/v6.14/