Data-driven optimization of MIG welding: A synergistic approach for superior joint quality

Abstract

A data-driven approach was applied in this research to determine input parameters for producing high-quality welds in mild steel sheets. By utilizing an L16 orthogonal array, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) techniques were utilized to optimize weld characteristics. The Multi-Objective Optimization based on Ratio Analysis (MOORA) method was used to rank these conflicting objectives according to their importance in different scenarios. From principal component analysis (PCA), setting the voltage at 42V, welding current at 250A, wire feed rate at 8 mm/min, and gas flow rate at 15 L/min results in ideal characteristics: penetration of 2.961 mm, reinforcement of 5.658 mm, bead width of 12.753 mm, and dilution percentage of 4.183%. Through the MOORA method, it was determined that a voltage of 40V, welding current of 175A, wire feed rate of 4 mm/min, and gas flow rate of 10 L/min would yield optimal weld bead geometry with penetration of 0.884 mm, reinforcement of 6.489 mm, bead width of 11.715 mm, and dilution percentage of 1.218%. This study effectively optimized welding parameters for superior welding in sheet metal fabrication for small and medium-sized enterprises.

Keywords

• MIG
• Taguchi method
• MOORA method
• PCA
• analysis of variance
• optimization

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