An expert system for predicting the deep drawing behavior of tailor welded blanks

The forming behavior of tailor welded blanks (TWB) is influenced by thickness ratio, strength ratio, and weld conditions in a synergistic fashion. In most of the cases, these parameters deteriorate the forming behavior of TWB. It is necessary to predict suitable TWB conditions for achieving better-stamped product made of welded blanks. This is practically difficult and resource intensive, requiring lot of simulations or experiments to be performed under varied base material and weld conditions. Automotive sheet part designers will be greatly benefited if an 'expert system' is available that can deliver forming behavior of TWB for varied weld and blank conditions. This work primarily aims at developing an expert system using artificial neural network (ANN) model to predict the deep drawing behavior of welded blanks made of steel grade and aluminium alloy base materials. The important deep drawing characteristics of TWB are predicted within chosen range of varied blank and weld conditions. Through out the work, PAM STAMP 2G(R) finite element (FE) code is used to simulate the forming behavior and to generate output data required for training the ANN. Predicted results from ANN model are compared and validated with FE simulation for two different intermediate TWB conditions. It is observed that the results obtained from ANN based expert system are encouraging with acceptable prediction errors.

[1]  Bernard Rolfe,et al.  Statistical analysis of finite element modeling in sheet metal forming and springback analysis , 2008 .

[2]  Ulaş Çaydaş,et al.  A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method , 2008 .

[3]  S. Bhole,et al.  FORMING BEHAVIOUR OF TAILOR (LASER) WELDED BLANKS OF AUTOMOTIVE STEEL SHEET , 2006 .

[4]  Tai-chiu Lee,et al.  Tailor-welded blanks of different thickness ratios effects on forming limit diagrams ☆ , 2003 .

[5]  Experimental and Theoretical Analysis on Formability of Aluminum Tailor-Welded Blanks , 2007 .

[6]  Kadir Çavdar,et al.  Development of a knowledge-based expert system for solving metal cutting problems , 2006 .

[7]  Brad L. Kinsey,et al.  An Analytical Model for Tailor Welded Blank Forming , 2003 .

[8]  R Ganesh Narayan,et al.  Weld Region Representation during the Simulation of TWB Forming Behavior , 2006 .

[9]  Michael Miles,et al.  Formability and strength of friction-stir-welded aluminum sheets , 2004 .

[10]  Robert H. Wagoner,et al.  Intelligent design environment: A knowledge based simulations approach for sheet metal forming , 1994 .

[11]  Peter Hodgson,et al.  Microstructural modeling of dynamic recrystallization using irregular cellular automata , 2008 .

[12]  Taylan Altan,et al.  Deep drawing of round cups from tailor-welded blanks , 1995 .

[13]  R. H. Wagoner,et al.  Forming of tailor-welded blanks , 1996 .

[14]  Klaus Pöhlandt,et al.  Formability of Metallic Materials , 2000 .

[15]  K. Narasimhan,et al.  Influence of the weld conditions on the forming-limit strains of tailor-welded blanks , 2008 .

[16]  P. Wild,et al.  On modeling of the weld line in finite element analyses of tailor-welded blank forming operations , 2004 .

[17]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[18]  Zhongxiao Peng,et al.  Expert system development for vibration analysis in machine condition monitoring , 2008, Expert Syst. Appl..

[19]  Eric Stein,et al.  A knowledge-based system to improve the quality and efficiency of titanium melting , 2003, Expert Syst. Appl..

[20]  K. Narasimhan,et al.  Relative Effect of Material and Geometric Parameters on the Forming Behaviour of Tailor Welded Blanks , 2007 .

[21]  M. Khaleel,et al.  Weld metal ductility in aluminum tailor welded blanks , 2000 .

[22]  R. Ganesh Narayanan,et al.  An expert system based on artificial neural network for predicting the tensile behavior of tailor welded blanks , 2009, Expert Syst. Appl..

[23]  Ghassan T. Kridli,et al.  Formability Improvement in Aluminum Tailor-Welded Blanks via Material Combinations☆ , 2004 .

[24]  Hisashi Kusuda,et al.  Formability of tailored blanks , 1997 .

[25]  C. L. Chow,et al.  Formability Analysis of Tailor-Welded Blanks of Different Thickness Ratios , 2005 .

[26]  Robert John Lark,et al.  The use of tailored blanks in the manufacture of construction components , 2001 .

[27]  B. Yegnanarayana,et al.  Artificial Neural Networks , 2004 .

[28]  J. Domińczuk,et al.  Modelling of adhesive joints and predicting their strength with the use of neural networks , 2008 .

[29]  R Ganesh Narayanan,et al.  Predicting the forming limit strains of tailor-welded blanks , 2008 .

[30]  Brad L. Kinsey,et al.  Comparison of Analytical Model to Experimental and Numerical Simulations Results for Tailor Welded Blank Forming , 2007 .

[31]  Youngmoo Heo,et al.  Characteristics of weld line movements for the deep drawing with drawbeads of tailor-welded blanks , 2001 .