Simulation based expert system to predict the deep drawing behaviour of tailor welded blanks

2012 ◽  
Vol 15 (3) ◽  
pp. 164 ◽  
Author(s):  
Abhishek T. Dhumal ◽  
R. Ganesh Narayanan ◽  
G. Saravana Kumar
Keyword(s):  
Expert System ◽  
Deep Drawing ◽  
Tailor Welded Blanks ◽  
Simulation Based

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

2010 ◽  
Vol 37 (12) ◽  
pp. 7802-7812 ◽  
Author(s):  
K. Veera Babu ◽  
R. Ganesh Narayanan ◽  
G. Saravana Kumar
Keyword(s):  
Expert System ◽  
Deep Drawing ◽  
Tailor Welded Blanks

Dynamic rescheduling using a simulation‐based expert system

2004 ◽  
Vol 15 (2) ◽  
pp. 199-212 ◽  
Author(s):  
Anand S. Kunnathur ◽  
P.S. Sundararaghavan ◽  
Sriram Sampath
Keyword(s):  
Expert System ◽  
Simulation Based ◽  
Dynamic Rescheduling

Prediction of Tensile Behavior of DP 590 Steel Tailor Welded Blanks by ANN

2011 ◽  
Vol 383-390 ◽  
pp. 1019-1026
Author(s):  
Susanta Kumar Dey ◽  
R. Ganesh Narayanan ◽  
Saravana Kumar Gurunathan
Keyword(s):  
Expert System ◽  
Base Material ◽  
Tensile Behavior ◽  
Strain Hardening Exponent ◽  
Prediction Errors ◽  
Tailor Welded Blanks ◽  
Weld Properties ◽  
Ann Models ◽  
Artificial Neural Network Ann ◽  
Full Factorial

The forming behavior of Tailor Welded Blanks (TWB) are greatly influenced by blank conditions like thickness ratio, strength ratio, weld conditions like weld orientation, weld location, and weld properties. 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 based on Artificial Neural Network (ANN) to predict the tensile behavior of TWBs made of DP 590 Steel grade base material. ANN models are developed based on full factorial and L27 orthogonal array design of experiments method and the results are compared. Through out the work, PAM STAMP 2G® finite element (FE) code is used to simulate the tensile behavior. The strain hardening exponent ‘n’ and strength co-efficient ‘K’ are predicted and used to train the ANNs. The results obtained from expert system/ANN models are validated by comparing them with the results obtained from FE simulations for chosen intermediate levels. The results are encouraging with acceptable prediction errors.

scholarly journals WELD MOVEMENT IN DEEP DRAWING OF TAILOR-WELDED BLANKS

2016 ◽  
Vol 2016 (05) ◽  
pp. 1309-1312
Author(s):  
Alexander Schrek ◽  
Pavol Svec ◽  
Veronika Gajdosova
Keyword(s):  
Deep Drawing ◽  
Tailor Welded Blanks

scholarly journals Effect of Thickness Ratio on Weld Line Displacement in Deep Drawing of Aluminium Steel Tailor Welded Blanks

2014 ◽  
Vol 6 ◽  
pp. 401-408 ◽  
Author(s):  
Arman Khan ◽  
V.V.N. Satya Suresh ◽  
Srinivasa Prakash Regalla
Keyword(s):  
Deep Drawing ◽  
Weld Line ◽  
Thickness Ratio ◽  
Tailor Welded Blanks
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