Optimization of stamping process parameters to predict and reduce springback and failure criterion

2014 ◽  
Vol 51 (2) ◽  
pp. 495-514 ◽  
Author(s):  
F.-Z. Oujebbour ◽  
A. Habbal ◽  
R. Ellaia
Keyword(s):  
Process Parameters ◽  
Failure Criterion ◽  
Stamping Process

scholarly journals Numerical investigation of key stamping process parameters influencing tool life and wear

2018 ◽  
Vol 15 ◽  
pp. 427-435 ◽  
Author(s):  
Shiva Shankar Mangalore Babu ◽  
Stuart Berry ◽  
Michael Ward ◽  
Michal Krzyzanowski
Keyword(s):  
Numerical Investigation ◽  
Tool Life ◽  
Process Parameters ◽  
Stamping Process

Optimization for Stamping Process Parameters of Front Fender Based on Numerical Simulation Technology

2010 ◽  
Vol 102-104 ◽  
pp. 232-236 ◽  
Author(s):  
Zhi Feng Liu ◽  
Qi Zhang ◽  
Wen Tong Yang ◽  
Jian Hua Wang ◽  
Yong Sheng Zhao
Keyword(s):  
Numerical Simulation ◽  
Sheet Metal ◽  
Process Parameters ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Simulation Analysis ◽  
Explicit Method ◽  
Simulation Technology ◽  
Stamping Process ◽  
Automotive Panel

According to the characteristic which is more and difficult to determine about the automotive panel forming factors, based on the dynamic explicit method, taking the typical automobile front fender for example, do the simulation analysis by using of DYNAFORM. On the premise of taking springback factors into account, analog the best stamping process parameters has been optimized from the analysis results after simulation such as sheet metal forming limited drawing(FLD)and sheet metal thinning drawing.

scholarly journals Influence of process parameters on deep drawing of 2060 Al–Li alloy under hot stamping process

2020 ◽  
Vol 3 (1) ◽  
pp. 36-42
Author(s):  
Xiaoming Yang ◽  
Baoyu Wang ◽  
Jing Zhou ◽  
Liming Dang ◽  
Wenchao Xiao ◽  
...  
Keyword(s):  
Process Parameters ◽  
Deep Drawing ◽  
Hot Stamping ◽  
Influence Of Process Parameters ◽  
Stamping Process

Numerical Analysis and Optimization of Stamping Technology for Electrical Motor’s Cover

2010 ◽  
Vol 97-101 ◽  
pp. 315-319 ◽  
Author(s):  
Bai Liu ◽  
Yong Quan Zhou ◽  
Ming Jun Liu ◽  
Zhen Yu Zhao
Keyword(s):  
Numerical Simulation ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Numerical Analysis ◽  
Plastic Flow ◽  
Process Parameters ◽  
Element Analysis ◽  
Elastic Plastic ◽  
Stamping Process

Based on Finite Element Analysis (FEA) module of Dynaform software, the paper made numerical simulation of a motor cover’s stamping process in the method of elastic-plastic flow, pointed out the behavior of deformation of stamping process, predicted and prevented stamping defect such as crack in the process, and calculated the degree of resilience. Consequently three forming numerical simulation schemes have been designed respectively, more feasible process parameters has been achieved in comparison with the features of each scheme.

Interlaboratory Comparison of Friction Conditions in Hot Stamping Operations

2010 ◽  
Vol 438 ◽  
pp. 97-105 ◽  
Author(s):  
Francesca Borsetto ◽  
Andrea Ghiotti ◽  
Stefania Bruschi ◽  
T. Stoehr ◽  
J. Lechler ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Process Parameters ◽  
Interlaboratory Comparison ◽  
Hot Stamping ◽  
Testing Procedures ◽  
Analysis Tools ◽  
Stamping Process

The paper presents results obtained at two labs, on in Germany and one in Italy, in terms of friction coefficient as function of hot stamping process parameters. Even if the testing procedures and analysis tools to evaluate tribological conditions are different for the two labs, both the approaches show a similar trend as regards the friction coefficient dependence from the process parameters.

Artificial Intelligence Optimization and Experimental Study of Auto Panel Stamping Process

2011 ◽  
Vol 55-57 ◽  
pp. 1794-1798
Author(s):  
Lin Zhou ◽  
Xiao Min Cheng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Process Parameters ◽  
Parameters Optimization ◽  
Nonlinear Material ◽  
Object Function ◽  
Stamping Process ◽  
Artificial Neural ◽  
Auto Panel

Auto panel stamping is a complicated plastic deformation process with geometry nonlinear, material nonlinearity and numerous process parameters. The stamping process of a typical auto panel wheel wrap was studied by artificial intelligent optimization and physical experiment. The prediction model of object function was established using artificial neural network. In object function, blank-holder force, drawbead height and fillet radius were selected as the optimized variables and prevention of rupture was considered as the optimization objective. Process parameters optimization was performed with genetic algorithm. The optimized process parameters were used to guide die design and testing, and the result of wheel wrap stamping showed that the forming quality was obviously improved. So the process optimization based on artificial neural network and genetic algorithm is feasible and efficient for auto panel stamping.

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