Probability density distribution-based evaluation of wire surface characteristics on metal transfer in GMAW

In recent industries, the use of robotic automation systems for arc welding has been continuously increasing to achieve higher speed and productivity. Accordingly, research on improving welding performance, such as enhancing arc stability and preventing spatter through the development of solid wires, has been actively conducted. In this study, a Probability Density Distribution (PDD)-based statistical framework is introduced to quantitatively evaluate arc stability and metal-transfer characteristics as a function of the manufacturing route of GMAW (Gas Metal Arc Welding) solid wires. High-speed camera imaging and welding monitoring signals were synchronized to capture metal-transfer behavior together with current and voltage data for six ER100S wires produced under different coating and surface-treatment conditions. Within the stable welding signal region (Stage 2), three distinct PDD curve patterns emerged depending on the predominant metal-transfer mode, appearing as pronounced peaks associated with concentrated current and voltage bands. Under identical current-input conditions, the effects of coating presence, coating weight, coating method, and special surface modifications were statistically compared. Notably, electroplated wires exhibited a markedly reduced PDD dispersion width by approximately 77% compared with chemically plated wires, demonstrating superior arc stability and a significantly lower probability of short-circuiting and spatter formation. These results indicate that the proposed PDD-based approach provides a quantitative tool for identifying key consumable-related factors governing arc stability and for guiding the development of reliable solid wires for robotic GMAW applications.