Title: Soft computing methods used for the modelling and optimisation of Gas Metal Arc Welding: a review

Authors: Kamal Pal, Surjya K. Pal

Addresses: Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India. ' Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India

Abstract: The quality of a weld primarily depends on the process parameters in any welding process. The welding parameters influence the weld bead geometry and weld microstructure, which is related to mechanical properties. It indicates the necessity to establish the relationship between process variables and weld quality characteristics. The Gas Metal Arc Welding (GMAW) processes are highly non-linear and coupled multivariable systems. It suggests the need for an intelligent system to evaluate the process and to determine the best adjustment. The soft computing techniques provide an alternative method for learning, predictive modelling, optimisation and control of weld quality without any mathematical model. This review illustrates the importance of soft computing tools for prediction, optimisation and control of GMAW processes.

Keywords: GMAW; gas metal arc welding; regression analysis; RSM; response surface methodology; ANNs; artificial neural networks; GAs; genetic algorithms; fuzzy logic; optimisation; modelling; weld quality; soft computing.

DOI: 10.1504/IJMR.2011.037911

International Journal of Manufacturing Research, 2011 Vol.6 No.1, pp.15 - 29

Published online: 09 May 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article