Selection of Optimum Welding Condition using Experimental Design Methods for the Automatic GMA Welding Process

Abstract

The welding parameters directly affect the weld forming and the joint performance in GMA (Gas Metal Arc) welding. Because of the many parameters involved in the automatic arc welding process, it is often not realistic to use traditional experimental methods such as full factorial design. Therefore, it is important to find the good experimental design method for determining the welding parameters that obtain an optimal joint quality with a minimal number of experiments. Therefore, this study is aimed at investigating the effect of DOE (Design of Experiment) methods on bead width of mild steel parts welded by the automatic GAM welding process. Taguchi method was employed to study effect the welding parameters and optimization of bead width, while Box-Behnken method was utilized to develop a mathematical model relating the bead width to welding parameters such as welding voltage, arc current, welding speed and CTWD (Contact Tip to Work Distance). The S/N (signal-to-noise) ratio and the ANOVA (Analysis of Variance) were employed to find the optimal bead width in automatic GAM welding process. Confirmation tests were carried out illustrating the effectiveness of the Taguchi method. The results showed that welding current mainly affected the bead width. The predicted bead width of 3.12mm was in agreement with the confirmation tests. With the regression coefficient analysis in the Box-Behnken design, a relationship between bead width and welding parameters was obtained. A second-order empirical model has also been established between the welding parameters and the bead width as welding quality. The developed model is adequate to navigate the design space.