A FINITE ELEMENT ANALYSIS FOR THE EFFECTS OF PROCESS PARAMETERS AND MATERIAL ANISOTROPY IN THE CYLINDRICAL DEEP DRAWING

2008 ◽  
Vol 07 (01) ◽  
pp. 21-32
Author(s):  
T. S. YANG ◽  
N. C. HWANG ◽  
R. F. SHYU

Deep drawing process, one of sheet metal forming methods, is very useful in industrial field because of its efficiency. The deep drawing process is affected by many material and process parameters, such as the strain-hardening exponent, plastic strain ratio, anisotropic property of blank, friction and lubrication, blank holder force, presence of drawbeads, the profile radius of die and punch, etc. In this paper, a finite element method is used to investigate the cylindrical deep drawing process. The thickness of product and the forming force predicted by current simulation are compared with the experimental data. A finite element method is also used to investigate the maximum forming load and the minimum thickness of products under various process parameter conditions, including the profile radius of die, the clearance between die cavity and punch and the blank holding force. Furthermore, the material anisotropy and process parameters effect on the earing are also investigated.

2015 ◽  
Vol 3 (1) ◽  
pp. 63-70 ◽  
Author(s):  
Ganesh M. Kakandikar ◽  
Vilas M. Nandedkar

Abstract Deep drawing is a forming process in which a blank of sheet metal is radially drawn into a forming die by the mechanical action of a punch and converted to required shape. Deep drawing involves complex material flow conditions and force distributions. Radial drawing stresses and tangential compressive stresses are induced in flange region due to the material retention property. These compressive stresses result in wrinkling phenomenon in flange region. Normally blank holder is applied for restricting wrinkles. Tensile stresses in radial direction initiate thinning in the wall region of cup. The thinning results into cracking or fracture. The finite element method is widely applied worldwide to simulate the deep drawing process. For real-life simulations of deep drawing process an accurate numerical model, as well as an accurate description of material behavior and contact conditions, is necessary. The finite element method is a powerful tool to predict material thinning deformations before prototypes are made. The proposed innovative methodology combines two techniques for prediction and optimization of thinning in automotive sealing cover. Taguchi design of experiments and analysis of variance has been applied to analyze the influencing process parameters on Thinning. Mathematical relations have been developed to correlate input process parameters and Thinning. Optimization problem has been formulated for thinning and Genetic Algorithm has been applied for optimization. Experimental validation of results proves the applicability of newly proposed approach. The optimized component when manufactured is observed to be safe, no thinning or fracture is observed.


2013 ◽  
Vol 40 (1) ◽  
pp. 125-130
Author(s):  
Trinet Yingsamphancharoen ◽  
Nakarin Srisuwan ◽  
Chira Densangarun

2008 ◽  
Vol 07 (01) ◽  
pp. 131-135
Author(s):  
TUNG-SHENG YANG ◽  
RUEY-FANG SHYU

Deep drawing process is very useful in industrial field because of its efficiency. The earing of deep drawing process is affected by many material and process parameters, such as the strain-hardening exponent, anisotropic property of blank, blank holder force, the profile radius of die, etc. In this paper, the material anisotropy and process parameters effect on the earing are investigated.


2014 ◽  
Vol 607 ◽  
pp. 112-117
Author(s):  
Khemajit Sena ◽  
Surasith Piyasin

This study aims to find a solution to improve the formability in a deep drawing process. For this purpose drawbeads were used to avoid wrinkles and ruptures. The finite element method was applied to simulate the 3D metal forming process using a die and drawbead. The drawbead amount, position, size and form were studied for their affects on the formability. 3 drawbead patterns with 3 different heights were examined. The simulation was performed for each drawbead pattern and each drawbead geometrical parameter and the failure elements were counted. The best pattern chosen was the pattern that resulted in the least failure elements.


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