Volume 22, Issue 2 (February 2022)                   Modares Mechanical Engineering 2022, 22(2): 121-132 | Back to browse issues page

‎ 20.1001.1.10275940.1400.22.2.4.7

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Deilami Azodi H, Rezaei S, Badparva H, Zeinolabedin Beygi A. Optimizing AA3105-St12 two-layer sheet in incremental sheet forming process using neural network and multi-objective genetic algorithm. Modares Mechanical Engineering 2022; 22 (2) :121-132
URL: http://mme.modares.ac.ir/article-15-53593-en.html
Optimizing AA3105-St12 two-layer sheet in incremental sheet forming process using neural network and multi-objective genetic algorithm
Hamed Deilami Azodi * 1, Saeed Rezaei2 , Hassan Badparva3 , Ali Zeinolabedin Beygi3
1- Associate Professor, Department of Mechanical Engineering, Arak University of Technology, Arak, Iran , hdazodi@arakut.ac.ir
2- M.Sc., Department of Mechanical Engineering, Arak University of Technology, Arak, Iran
3- M.Sc. Student, Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran
Abstract:   (2460 Views)
Incremental sheet forming is a flexible forming technology in which the sheet metal is gradually formed by the movement of tools in specified path. Due to the progressively localized deformation of the sheet and concentration of the forces on contact area of tool and sheet metal, the formability of the sheet increases compared with other common forming methods. In this study, numerical simulation of the incremental forming of AA3105-St12 two-layer sheet has been performed to calculate forming force and final thicknesses of the layers. The validity of the simulation results is evaluated by comparing them with those obtained from experiments. Numerical models for estimating the vertical force applied on the tool and the final thicknesses of the layers in terms of the process variables have been obtained using artificial neural network. Multi-objective optimization has been conducted to achieve the minimum force and the minimum thickness reduction of layers using obtained numerical models based on genetic algorithm method. Optimum thickness of the two-layer sheet and the thickness ratio the layers in different states of contact of the aluminum or the steel layers with the forming tool have been determined.
Keywords: metal forming, incremental sheet forming, neural network, multi-objective optimization, genetic algorithm
Full-Text [PDF 1051 kb]   (1584 Downloads)    
Article Type: Original Research | Subject: Forming of metal sheets
Received: 2021/06/26 | Accepted: 2021/09/14 | Published: 2022/01/30
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