3D modeling of shear-slitting process for aluminum alloys

Abstract This work combines experimental studies with finite element simulations to develop a reliable numerical model for simulating the important shearing process in aluminum alloys. Burr formation in shearing is of critical concern with respect to the quality of the product. The paper discusses various aspects leading to the modeling of the shearing process with an aim to design process parameters for burr reduction. Three damage models are implemented in the finite element model for simulating the shearing process. Experiments with macroscopic and microscopic observations are used to characterize the material quantitatively and to calibrate the constitutive and damage models. The user material subroutine VUMAT is used for implementation of material and damage models in the commercial finite element code ABAQUS. Parametric studies are finally conducted to study the effect of process parameters on the shearing process and especially on burr formation.

[1]  S. Shima,et al.  Criteria for ductile fracture and their applications , 1980 .

[2]  A. Atkins,et al.  On cropping and related processes , 1980 .

[3]  S. Clift,et al.  Fracture prediction in plastic deformation processes , 1990 .

[4]  J. Lemaître A CONTINUOUS DAMAGE MECHANICS MODEL FOR DUCTILE FRACTURE , 1985 .

[5]  Josef Reissner,et al.  Optimization of sheet-metal forming processes using the special-purpose program AUTOFORM , 1995 .

[6]  Ming Li,et al.  An experimental investigation on cut surface and burr in trimming aluminum autobody sheet , 2000 .

[7]  N. Aravas On the numerical integration of a class of pressure-dependent plasticity models , 1987 .

[8]  Fpt Frank Baaijens,et al.  Evaluation of ductile fracture models for different metals in blanking , 2001 .

[9]  John Monaghan,et al.  Failure analysis of cold forging dies using FEA , 2001 .

[10]  V. Tvergaard Material Failure by Void Growth to Coalescence , 1989 .

[11]  A. Atkins,et al.  Surfaces produced by guillotining , 1981 .

[12]  Ridha Hambli,et al.  Finite element model fracture prediction during sheet-metal blanking processes , 2001 .

[13]  José Divo Bressan,et al.  A computational approach to blanking processes , 2002 .

[14]  Fpt Frank Baaijens,et al.  Discrete ductile fracture modelling for the metal blanking process , 2000 .

[15]  Fpt Frank Baaijens,et al.  Predicting the shape of blanked products: a finite element approach , 2000 .

[16]  H. H. Wisselink,et al.  Simulation of the slitting process with the finite element method , 1999 .

[17]  Somnath Ghosh,et al.  A new approach to optimal design of multi-stage metal forming processes with micro genetic algorithms , 1997 .

[18]  Moriya Oyane,et al.  Criteria of Ductile Fracture Strain , 1972 .

[19]  Ming Li,et al.  Micromechanisms of deformation and fracture in shearing aluminum alloy sheet , 2000 .

[20]  Tomasz Wierzbicki,et al.  A tension zone model of blanking and tearing of ductile metal plates , 1996 .

[21]  J. Chung,et al.  Application of a genetic algorithm to process optimal design in non-isothermal metal forming , 1998 .

[22]  Taylan Altan,et al.  Material fracture and burr formation in blanking results of FEM simulations and comparison with experiments , 1996 .

[23]  U. P. Singh,et al.  Finite element simulation of the punching/blanking process using in-process characterisation of mild steel , 2003 .

[24]  F. A. McClintock,et al.  A Criterion for Ductile Fracture by the Growth of Holes , 1968 .

[25]  Owen Richmond,et al.  Three dimensional characterization and modeling of particle reinforced metal matrix composites: part I Quantitative description of microstructural morphology , 1999 .

[26]  Anthony G. Atkins,et al.  On the mechanics of guillotining ductile metals , 1990 .

[27]  D. M. Tracey,et al.  On the ductile enlargement of voids in triaxial stress fields , 1969 .

[28]  Gang Fang,et al.  Finite element simulation of the effect of clearance on the forming quality in the blanking process , 2002 .

[29]  R. Hambli Prediction of burr height formation in blanking processes using neural network , 2002 .