Modeling and optimization of flux cored arc welding by genetic algorithm and simulated annealing algorithm

Abstract

Purpose

The purpose of this study is to optimize the process parameters (wire feed rate (F), voltage (V), welding speed (S) and torch angle (A)) in order to obtain the optimum bead geometry (bead width (W), reinforcement (R) and depth of penetration (P)), considering the ranges of the process parameters using evolutionary algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm.

Design/methodology/approach

The modeling of welding parameters in flux cored arc welding process using a set of experimental data and regression analysis, and optimization using GA and SA algorithm.

Findings

The adequate mathematical model was developed. The multiple objectives were optimized satisfactorily by the GA and SA algorithms. The feasible solution results are very closer to the optimized results and the percentage error was found to be negligibly small.

Originality/value

The optimal welding parameters were identified in order to increase the productivity. The welding input parameters effect was found.

Citation

Katherasan, D., V. Elias, J., Sathiya, P. and Noorul Haq, A. (2013), "Modeling and optimization of flux cored arc welding by genetic algorithm and simulated annealing algorithm", Multidiscipline Modeling in Materials and Structures, Vol. 9 No. 3, pp. 307-326. https://doi.org/10.1108/MMMS-03-2012-0008