Controlling heat input (HI) in welding is critical for ensuring joint quality and preventing defects, yet existing models often fail to account for the complex interactions between current, voltage, and welding speed. This study addresses this gap by developing a predictive model to optimize HI, focusing on gas metal arc welding (GMAW) of low-carbon steel. The aim was to establish precise parameter combinations that balance thermal input with weld integrity, particularly for industrial applications requiring controlled heat management. A central composite design (CCD) within Response Surface Methodology (RSM) was employed, systematically varying current (180–240 A), voltage (18–24 V), and welding speed (70–100 mm/min). Heat input was calculated using the standard HI formula, and a quadratic regression model was developed and validated through ANOVA, lack-of-fit tests, and diagnostic metrics. The models robustness was confirmed with R² = 0.9933 and Adeq. Precision = 46.561, ensuring reliability for industrial use. The results identified voltage as the most influential parameter (ip 0.0001/i), with optimal conditions (200 A, 21.07 V, 70 mm/min) achieving HI = 1.24 kJ/mm and 87.5% desirability. The study demonstrates that controlled voltage-speed interactions are key to minimizing HI while maintaining joint quality. These findings provide actionable insights for welding optimization, recommending future expansion to high-alloy materials and real-time HI monitoring for broader industrial adoption.
Oruowho et al. (Sat,) studied this question.