Numerical Modelling and Simulation of Sheet Metal Forming Process

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY

International Journal of Mathematical Engineering and Management Sciences Pub Date : 2023-04-30 DOI:10.21791/ijems.2023.1.1.

Marwen Habbachi, A. Baksa

引用次数: 0

Abstract

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.

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板料成形过程的数值模拟与仿真

金属板成形过程的仿真和建模在不同的行业(汽车，航空航天)和几个研究中心都很常见，因为它对设备生命周期的生产和可靠性以及产品质量都有巨大的影响。然而，为了使输入参数获得尽可能最佳的配置，以达到高产量和增加工具的耐用性，需要一些额外的方法来优化这一问题，主要采用有限元法与基于人工神经网络(ANN)的迭代算法相结合的方法[1]。本研究主要针对不锈钢AISI 304冲压成形过程进行建模，研究材料的成形性，并研究摩擦系数对产品质量的影响，以及每组配置所需的能量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Mathematical Engineering and Management Sciences Multiple-

CiteScore

3.80

自引率

6.20%

发文量

审稿时长

20 weeks

期刊介绍： IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.

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