Flux Cored Arc Welding Parameter Optimization Using Particle Swarm Optimization Algorithm

Abstract Flux cored arc welding (FCAW) process is a fusion welding process in which the welding electrode is a tubular wire that is continuously fed to the weld area. It is widely used in industries and shipyards for welding heavy plates. Welding input parameters play a very significant role in determining the quality of a weld joint. This paper addresses the modeling of welding parameters in FCAW process using a set of experimental data and regression analysis, and optimization using Particle Swarm Optimization (PSO) Algorithm. The input process variables considered here include wire feed rate (F); voltage (V); welding speed (S) and torch Angle (A) each having 5 levels. The process output characteristics are weld bead width, reinforcement and depth of penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. In the next stage, the proposed model is embedded into PSO algorithm to optimize the FCAW process parameters. In this study the objectives considered are maximization of depth of penetration, minimization of bead width and minimization of reinforcement. A comparative study on the effectiveness of the two algorithms on the optimization of the weld bead geometry is done

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