Investigation And Optimization Of Mig Welding Parameters On The Mechanical Properties Of Mild Steel Using Response Surface Methodology

Abstract

Metal Inert Gas (MIG) welding is extensively employed in structural and industrial applications due to its efficiency and adaptability; however, improper selection of welding parameters often results in internal defects such as porosity, lack of fusion, and incomplete penetration, which significantly degrade mechanical performance and compromise structural safety. A documented failure of welded joints emphasized the necessity for systematic defect investigation and process optimization. Consequently, this study focuses on the investigation and optimization of MIG welding parameters to improve weld integrity and mechanical performance of low-carbon steel joints. An integrated experimental methodology combining non-destructive testing (NDT), destructive mechanical testing, and statistical optimization was employed. Ultrasonic testing (UT), dye penetrant testing, magnetic particle inspection, and electromagnetic yoke testing were used to identify surface and subsurface defects, while tensile and hardness tests quantified mechanical behavior across the weld zone (WZ) and heat-affected zone (HAZ). Response Surface Methodology (RSM) with a Design of Experiments (DOE) framework comprising 32 experimental runs was applied to optimize welding current, voltage, and travel speed. Desirability Function Analysis (DFA) was utilized to determine the optimum multi-response parameter combination. The optimized MIG welding parameters obtained through DFA yielded a global desirability close to unity, indicating simultaneous enhancement of all response variables. At the optimum condition, the predicted mechanical properties were a yield strength of approximately 400 MPa, ultimate tensile strength (UTS) of about 495 MPa, strain at fracture of approximately 22%, and hardness values of roughly 91 HRB in the weld zone and 86 HRB in the HAZ. Experimental verification tests closely matched the predicted results, with deviations within ±2%, confirming the adequacy and reliability of the developed models. Ultrasonic evaluation further revealed that optimized welds exhibited higher echo amplitudes, sharper signal responses, reduced noise levels, and stronger backwall reflections compared to the old welds, indicating reduced internal defects and improved acoustic continuity. The strong agreement between predicted and experimental results validates the effectiveness of RSM-DFA-based optimization. The findings confirm that ultrasonic testing is a robust tool for weld quality assessment and process validation, and the proposed optimization framework provides practical guidance for producing defect-minimized, structurally reliable MIG-welded joints in critical engineering applications.