Prediction of Wrinkling and Determination of Minimum Blankholding Pressure in Multistage Deep Drawing

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Anupam Agrawal ◽  
N. Venkata Reddy ◽  
P. M. Dixit
Keyword(s):  
Upper Bound ◽  
Deep Drawing ◽  
Maximum Amplitude ◽  
Thickness Variation ◽  
Process Conditions ◽  
Blank Holder ◽  
Analysis Methodology ◽  
Wrinkling Analysis ◽  
Process Constraints

Wrinkling in the flange region has been observed during redrawing operation by a few researchers. In the present work an analysis methodology, based on a combination of upper bound and energy approaches, is proposed for the prediction of number of wrinkles and minimum blankholding pressure necessary to avoid wrinkling in redrawing operation. Thickness variation predicted by the upper bound formulation is used as input for the wrinkling analysis by assuming a suitable waveform based on geometrical and process conditions. The flange is constrained at both ends, i.e., by the blank holder profile radius and at the die entry point (where the sheet enters into the die cavity). The waveform for present analysis is assumed such that it has zero displacement at both ends (since it is constrained) and the maximum amplitude of the wave at some point in between those ends. The wrinkling predicted by the present methodology seems to be reasonably accurate considering the geometrical and process constraints of the redraw.

Determination of Minimum Blankholding Pressure for Producing Wrinkle Free Products in Multistage Deep Drawing

2011 ◽  
Author(s):  
Anupam Agrawal ◽  
N. Venkata Reddy ◽  
P. M. Dixit
Keyword(s):  
Upper Bound ◽  
Maximum Amplitude ◽  
Thickness Variation ◽  
Process Conditions ◽  
Free Products ◽  
Blank Holder ◽  
Analysis Methodology ◽  
Wrinkling Analysis ◽  
Process Constraints

Wrinkling in the flange region has been observed during redrawing operation by few researchers. In the present work an analysis methodology, based on a combination of upper bound and energy approaches, is proposed for the prediction of number of wrinkles and minimum blankholding pressure necessary to avoid wrinkling in redrawing operation. Thickness variation predicted by the upper bound formulation is used as input for the wrinkling analysis by assuming a suitable waveform based on geometrical and process conditions. The flange is constrained at both the ends, i.e. by the blank holder profile radius and at the die entry point (where the sheet enters into the die cavity). The waveform for present analysis is assumed such that it has zero displacement at both the ends (since it is constrained) and the maximum amplitude of the wave at some point in between those ends. The wrinkling predicted by the present methodology seems to be reasonably accurate considering the geometrical and process constraints of the redraw.

Optimization of segmented variable blank holder force for minimizing the thickness variation in deep drawing

2016 ◽  
Vol 2016.12 (0) ◽  
pp. 1209
Author(s):  
Hiroki KOYAMA ◽  
Satoshi KITAYAMA ◽  
Kiichiro KAWAMOTO ◽  
Takuji MIYASAKA ◽  
Takuya NODA ◽  
...  
Keyword(s):  
Deep Drawing ◽  
Thickness Variation ◽  
Blank Holder Force ◽  
Blank Holder ◽  
Variable Blank Holder Force

Deep Drawing of Square-Shaped Sheet Metal Parts, Part 2: Experimental Study

1993 ◽  
Vol 115 (1) ◽  
pp. 110-117 ◽  
Author(s):  
S. A. Majlessi ◽  
D. Lee
Keyword(s):  
Process Parameters ◽  
Deep Drawing ◽  
Process Conditions ◽  
Drawing Process ◽  
Blank Holder Force ◽  
Blank Holder ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Punch Load ◽  
Blank Size

The deep drawing process of square and rectangular shells were investigated under different process conditions, and using two different drawing quality steels. The main objective was to identify the significance of some of the process parameters on the outcome of the drawing operation. The process parameters examined were shape and size of blank, the blank-holder force and frictional condition between blank and tooling. The results of this investigation were presented in terms of punch load, through thickness and in-plane strain distributions, formations of flange wrinkles and fracture, and the largest possible blank size that can be drawn successfully. Some of these experimental results were used to verify the validity of a simplified analytical model which was described in the first part of this paper.

Experimental Estimation of Size Effect and Formability in Microscale Deep Drawing Process Using Copper Sheet

2014 ◽  
Author(s):  
Jung Soo Nam ◽  
Sang Won Lee ◽  
Hong Seok Kim
Keyword(s):  
Deep Drawing ◽  
Metal Sheet ◽  
Process Conditions ◽  
Drawing Process ◽  
Copper Sheet ◽  
Feature Size ◽  
Blank Holder ◽  
Deep Drawing Process ◽  
Plastic Deformation Behavior ◽  
Tooling System

In this study, the size dependence of metal sheet on the plastic deformation behavior was investigated in microscale deep drawing process. In order to perform deep drawing experiments, a tooling system was first developed. Then, a series of microscale deep drawing experiments were performed in various process conditions. The blank holder gap between the blank and blankholder was controlled to eliminate the possible defect such as wrinkling. In particular, the effects of feature size were analyzed by comparing the normalized deformation loads at different values of the scale factor λ. It was found that the maximum value of the normalized deformation load and the failure instant were strongly influenced by the feature size of metal sheet.

Experimental Determination of Heat Transfer Coefficients for Forming of Stainless Steel Sheets Considering Process Conditions and Deep-Drawing Film

2013 ◽  
Vol 554-557 ◽  
pp. 1501-1508 ◽  
Author(s):  
Philipp Schmid ◽  
Mathias Liewald
Keyword(s):  
Heat Transfer ◽  
Stainless Steel ◽  
Deep Drawing ◽  
Basic Knowledge ◽  
Process Conditions ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Steel Sheets ◽  
Forming Tools

Heat transfer coefficients are playing an important role in forming of metastable stainless steel sheets. Metastable austenitic stainless steels are highly influenced by heating of forming tools due to generation of latent heat during forming process. Strain-induced martensite formation and hence the TRIP-effect is directly coupled with the temperature development within forming tools as well as the temperature induced by heat controlled tools. Measurements of heat development in serial deep drawing processes are showing the need for an accurate determination of heat transfer coefficients considering actual process conditions. Heat transfer coefficients were determined with a simple and easy applicable measurement device for tool materials AMPCO 25 and cold work tool steel EN 1.2379 in combination with aluminum, austenitic EN 1.4301 and ferritic EN 1.4016 stainless steel grades. Special attention was paid to production-related individual influences such as surface conditions, lubrication and deep drawing film. Experiments were accomplished between 1-15 N/mm² showing high influence of intermediate media on heat transfer between forming tool and part and serve as boundary conditions for fully thermo-mechanical coupled forming simulations. A strong influence of deep drawing film, lubrication and surface pressure on heat exchange could be determined and this basic knowledge is seen as mandatory for dimensioning of heat controlled metal forming tools. Finally the experimental determined results are discussed and compared to common heat transfer models and similar experiments from literature.

scholarly journals Surrogate model–based inverse parameter estimation in deep drawing using automatic knowledge acquisition

2021 ◽  
Author(s):  
Matthias Ryser ◽  
Felix M. Neuhauser ◽  
Christoph Hein ◽  
Pavel Hora ◽  
Markus Bambach
Keyword(s):  
Knowledge Acquisition ◽  
Process Parameters ◽  
Deep Drawing ◽  
Blank Holder ◽  
Target Values ◽  
Simulation Based ◽  
Column Subset Selection ◽  
Automatic Knowledge Acquisition ◽  
Sensor Signals

AbstractIn this paper, we propose a new approach for the simulation-based support of tryout operations in deep drawing which can be schematically classified as automatic knowledge acquisition. The central idea is to identify information maximising sensor positions for draw-in as well as local blank holder force sensors by solving the column subset selection problem with respect to the sensor sensitivities. Inverse surrogate models are then trained using the selected sensor signals as predictors and the material and process parameters as targets. The final models are able to observe the drawing process by estimating current material and process parameters, which can then be compared to the target values to identify process corrections. The methodology is examined on an Audi A8L side panel frame using a set of 635 simulations, where 20 out of 21 material and process parameters can be estimated with an R2 value greater than 0.9. The result shows that the observational models are not only capable of estimating all but one process parameters with high accuracy, but also allow the determination of material parameters at the same time. Since no assumptions are made about the type of process, sensors, material or process parameters, the methodology proposed can also be applied to other manufacturing processes and use cases.

Determination of Proper Loading Profiles for Hydro-Mechanical Deep Drawing Process Using FEA

2014 ◽  
Vol 686 ◽  
pp. 540-548
Author(s):  
S.B. Akay ◽  
E.F. Şükür ◽  
M. Turkoz ◽  
S. Halkaci ◽  
M. Koç ◽  
...  
Keyword(s):  
Deep Drawing ◽  
Manufacturing Process ◽  
Sheet Material ◽  
Fluid Pressure ◽  
Process Conditions ◽  
Hydraulic Pressure ◽  
Drawing Ratio ◽  
Blank Holder Force ◽  
Blank Holder ◽  
Force Profiles

Hydro-mechanical Deep Drawing (HMD) is an advanced manufacturing process developed to form sheet metal blanks into complex shapes with smooth surfaces using hydraulic pressure as an additional source of deformation force. There are many factors affecting the successful production of desired parts using this manufacturing process. The most important factors are the fluid pressure and blank holder force. Having proper values of these parameters during forming has a direct impact on part properties such as drawing ratio and thinning. In order to determine desired the fluid pressure and blank holder force profiles, which are different for every geometry, material and other process conditions, finite element simulations are conducted to save time and cost. Abaqus FEA software is used in this study. In order to define the continuously changing fluid pressure application area on the sheet material, which is not an available module or standard interface of software, sub-programs (sub-routines) are developed to properly and dynamically define the fluid pressure area. Proper, if not optimal, fluid pressure and blank holder force profiles, which allow the formability (LDR) of sheet material to be maximum, were obtained using trial and error method. Maximum thinning values on metal blank were used as a control parameter to determine if selected loading profiles result in the highest LDR with lowest thinning.

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