Experimental Evaluation of Arc Stud Welding Techniques on Structural and Stainless Steel: Effects on Penetration Depth and Weld Quality
Source abstract
Abstract
Arc stud welding differs from conventional arc welding techniques and is widely used for joining structural steel, stainless steel, aluminum, and copper alloys in various configurations. Achieving a reliable stud weld requires appropriate welding parameters and a suitable process selection, considering factors such as stud diameter, base material, and surface condition. This study experimentally compares three arc stud welding techniques—arc welding with a ceramic ferrule (ARC CF), arc welding with shielding gas (ARC SG), and arc welding assisted by a radially symmetric magnetic field (ARC SRM)—applied to structural steel (1.0038) and stainless steel (1.4301). Macrostructural analysis, Vickers hardness testing (HV10), visual inspection, non-destructive testing, and bend tests were performed to evaluate weld quality. Results show that ARC CF achieved the highest penetration and hardness but produced more spatter. ARC SG provided moderate penetration but was more prone to cold welds, while ARC SRM resulted in the cleanest collars with minimal spatter but shallower penetration. All welds met ISO 5817:2014 Quality Level C, confirming acceptable structural integrity. These findings support informed selection and optimization of stud welding techniques for diverse engineering applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Material Selection and Properties · Welding Techniques and Residual Stresses · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechatronics, University North, 48000 Koprivnica, Croatia
Department of Mechanical Engineering, Zagreb University of Applied Science, 10000 Zagreb, Croatia
Funding
Analysis of Surface Parameters of Metal Coatings Applied to Polymer Structures Manufactured by Additive Technology Using Computer Vision (APPMPPTRV)
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