A Rapid Inverse Method of Material Performance Parameters in Sheet Metal Forming

2012 ◽  
Vol 538-541 ◽  
pp. 1035-1040
Author(s):  
Hua Liu ◽  
Kai Yong Jiang ◽  
Bin Liu ◽  
Ping Lu
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Inverse Method ◽  
Orthogonal Experiment ◽  
The Self ◽  
Performance Parameters ◽  
Sensitive Material ◽  
Material Parameters

This paper proposes a fast and convenient method to inverse the material performance parameters in stamping forming. This method effectively combined with the FEM and the genetic algorithm. The reverse objective function was constructed with the thickness which is easily measured from the stamped parts, and then a genetic algorithm was programmed; The thickness-sensitive material performance parameters can be acquired through the orthogonal experiment, then these material parameters can be inversed by the self-programming genetic algorithm. Finally, a stamping case proves this method is precise, rapid and valid.

A Contribution to the Optimisation of a Simple Shear Test

2009 ◽  
Vol 410-411 ◽  
pp. 467-472 ◽  
Author(s):  
Marion Merklein ◽  
M. Biasutti
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Shear Test ◽  
The Finite Element Method ◽  
Simple Shear Test ◽  
Material Parameters

The finite element method is a widely used tool in sheet metal forming. The quality of the results of such an analysis depends largely on the applied constitutive model and its material parameters, which have to be determined experimentally. These data are relevant on the choice of the yield criterion among the wide range of options available in the commercial applications implementing the finite element method. Since the accuracy of material parameters estimation is therefore crucial, investigations were performed with an Al-Mg sheet alloy and a mild steel sheet to optimize a Miyauchi-based simple shear test. This method is one of the basic ways to investigate the plastic properties of a sheet metal up to large strains, which is very important for numerical analysis of sheet metal forming processes. Aim of the test is to determine the shear stress-strain correlation. In order to enhance the quality of the experimental results the detection of the deformation’s field, trough an optical measurement system, and the methodology for its evaluation are focus of the present study.

Effect of Material Parameters Wave on Sheet Metal Springback Using Orthogonal Design Simulation

2011 ◽  
Vol 314-316 ◽  
pp. 585-588 ◽  
Author(s):  
Lei Chen
Keyword(s):  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Orthogonal Design ◽  
Direct Analysis ◽  
Element Model ◽  
Internal Stresses ◽  
Common Phenomenon ◽  
Material Parameters ◽  
Simulation Results

Springback is a common phenomenon in sheet metal forming, caused by the elastic redistribution of the internal stresses during unloading. The aim of this search is to investigate the wave of material parameters on the results of forming and springback of sheet metal. A finite element model of cylinder bending benchmark of NUMISHEET’2002 was proposed firstly to simulate bending and springback with contact evolution between tools and blank based on static implicit method. The simulation results agree well with the experiment. Then the effects of the wave of material parameters on forming and springback results are investigated using orthogonal design simulation. Eight factors are investigated with the orthogonal label. The results show the factors have different effects on both the forming and springback. And the significance of the factors is shown through direct analysis of the results.

Intelligent Multi-Objective Optimization for High Strength Sheet Metal Forming Process of Body Part

2012 ◽  
Vol 455-456 ◽  
pp. 1515-1520
Author(s):  
Zhi Guo An ◽  
Yu Zhang
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
High Strength ◽  
Body Part ◽  
Multi Objective Optimization ◽  
Forming Process ◽  
Multi Objective ◽  
Metal Forming Process

In high strength sheet metal forming process of body part, crack, wrinkle and severe thinning are the main faults usually. The degree of the faults varies with the change of input process parameters. Optimization for sheet metal forming process of body part is often considered as a multi-objective problem. Design of experiment method and genetic algorithm are often combined together to cope with this multi-objective optimization problem. High strength steel sheet metal forming process is relatively complex and difficult. An intelligent multi-objective optimization strategy for high strength sheet metal forming process was suggested based on genetic algorithm. Latin Hypercube Sampling method was introduced to design the rational experimental samples; the objective function was defined based on crack factor, wrinkle factor and severe thinning factor; the accurate response surface model for sheet metal forming problem was built; Multi-objective genetic algorithm was adopted in optimization and Pareto solution was selected. The strategy was applied to analyze a rocher. The result has proved this strategy suitable for optimization design of sheet metal forming process .

An image-driven uncertainty inverse method for sheet metal forming problems

2021 ◽  
pp. 1-52
Author(s):  
Yu Li ◽  
Hu Wang ◽  
Biyu Li ◽  
Jiaquan Wang ◽  
Enying Li
Keyword(s):  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Material Flow ◽  
Inverse Method ◽  
Approximate Bayesian Computation ◽  
Design Parameters ◽  
Sufficient Statistics ◽  
Margin Of Safety ◽  
Approximate Bayesian

Abstract The purpose of this study is to obtain a margin of safety for material and process parameters in sheet metal forming. Commonly applied forming criteria are difficult to comprehensively evaluate the forming quality directly. Therefore, an image-driven criterion is suggested for uncertainty parameter identification of sheet metal forming. In this way, more useful characteristics, material flow, and distributions of safe and crack regions, can be considered. Moreover, to improve the efficiency for obtaining sufficient statistics of Approximate Bayesian Computation (ABC), a manifold learning-assisted ABC uncertainty inverse framework is proposed. Based on the framework, the design parameters of two sheet metal forming problems, an air conditioning cover and an engine inner hood, are identified.

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