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

Authors: Abhishek T. Dhumal; R. Ganesh Narayanan; G. Saravana Kumar

Addresses: Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781 039, Assam, India. ' Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati 781 039, Assam, India. ' Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India

Abstract: The forming behaviour of tailor welded blanks (TWB) is influenced by sheet thickness ratio, strength ratio and weld conditions in a synergistic fashion. In most of the cases, these parameters deteriorate the forming behaviour of TWB. It is necessary to predict suitable TWB conditions for achieving better stamped product made of welded blanks. This work primarily aims at developing an expert system based on artificial neural network (ANN) model to predict the deep drawing behaviour of TWBs made of steel grade base materials. The important deep drawing characteristics of TWB namely maximum draw depth and weld line profile are predicted within wide range of varied blank and weld conditions. The square cup deep drawing test is simulated in an elastic-plastic finite element code, PAM STAMP 2G®, generating the required output data for ANN training and validation. The predictions from ANN are encouraging with acceptable prediction errors.

Keywords: tailor welded blanks; TWB; forming behaviour; expert systems; neural networks; modelling; simulation; deep drawing; steel; maximum draw depth; weld line profile.

DOI: 10.1504/IJMIC.2012.045689

International Journal of Modelling, Identification and Control, 2012 Vol.15 No.3, pp.164 - 172

Published online: 29 Nov 2014 *

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