Table of Contents
International Journal of Manufacturing Engineering
Volume 2013 (2013), Article ID 230463, 17 pages
Research Article

Fuzzy Logic-Based Techniques for Modeling the Correlation between the Weld Bead Dimension and the Process Parameters in MIG Welding

Soft Computing Lab., Mechanical Engineering Department, Indian Institute of Technology, Kharagpur 721 302, India

Received 11 March 2013; Accepted 14 August 2013

Academic Editors: G. Onwubolu, N. Rezg, and K. Salonitis

Copyright © 2013 Y. Surender and Dilip Kumar Pratihar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Fuzzy logic-based techniques have been developed to model input-output relationships of metal inert gas (MIG) welding process. Both conventional and hierarchical fuzzy logic controllers (FLCs) of Mamdani type have been developed, and their performances are compared. The conventional FLC suffers from the curse of dimensionality for handling a large number of variables, and a hierarchical FLC was proposed earlier to tackle this problem. However, in that study, both the structure and knowledge base of the FLC were not optimized simultaneously, which has been attempted here. Simultaneous optimization of the structure and knowledge base is a difficult task, and to solve it, a genetic algorithm (GA) will have to deal with the strings having varied lengths. A new scheme has been proposed here to tackle the problem related to crossover of two parents with unequal lengths. It is interesting to observe that the conventional FLC yields the best accuracy in predictions, whereas the hierarchical FLC can be computationally faster than others but at the cost of accuracy. Moreover, there is no improvement of interpretability by introducing a hierarchical fuzzy system. Thus, there exists a trade-off between the accuracy obtained in predictions and computational complexity of various FLCs.