An Optimization Comparison between Taguchi Based GRA and DFA for Dissimilar Welding Made by GTAW

Saleh Suliman Saleh  Elfallah

doi:10.66411/jer.v41i2.112

Authors

Saleh Suliman Saleh Elfallah College of Mechanical Engineering Technology, Benghazi, Libya Author

DOI:

https://doi.org/10.66411/jer.v41i2.112

Keywords:

GTAW, mechanical properties, dissimilar welding, Taguchi, GRA, DFA

Abstract

Dissimilar metal welding is commonly performed using Gas Tungsten Arc Welding (GTAW), particularly for joining stainless steel and low-carbon steel in applications such as power plants, heat exchanger assemblies, pipeline construction and, automobile manufacturing. However, dissimilar welding is a delicate and more challenging process than homogeneous welding due to differences in the mechanical and metallurgical properties of the base metals. Welding parameters such as welding speed, welding current, shielding gas flow rate, and filler metal type have a significant influence on the quality of the final weldment. Therefore, optimization of these parameters is essential to achieve reliable weld performance. In industrial practice, various single and multi-objective optimization techniques, including DoE and artificial intelligence based methods employed to optimize welding parameters. This study compares Taguchi-based GRA and DFA as multi-objective optimization techniques for GTAW dissimilar welding of AISI 304 stainless steel and EN10130 mild steel. The welding parameters investigated include welding current, shielding gas composition, and welding filler size. The results have shown that GRA and DFA have concluded that weldment with parametric combination of 120 A, 2.5 mm welding filler and pure Ar shielding gas has shown optimal setting. The Taguchi-based GRA exhibited 0 % prediction error for the optimal combination prediction indicating excellent and highly reliable model, while a concluded DFA error of 4.25 % validates the model accuracy as acceptable.

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