Hybrid Multi Objectives Optimization Based (TIB -LIB) Constraints to Optimizing GTAW Parameters for Enhancing Microstructure
Abstract:
This study presents an integrated optimization framework for Tungsten Inert Gas (TIG) welding of AISI 316L stainless steel, combining factorial design, (ANOVA), 2FI model, and DFA to achieve simultaneous optimi zation of hardness and impact toughness. The hybrid multi-objective approach establishes predictive models validated through experimental confirmation tests to ensure accuracy and consistency of results. Full factorial design experiments were conducted to evaluate the influence of welding current, voltage, and gas flow rate on weld quality. ANOVA results indicated that welding current and voltage were the most significant factors af fecting mechanical properties. Using the desirability function, the multi-response objectives were consolidated into a single optimization metric, achieving a composite desirability of welding joint performance of 0.90. Optimal parameters of 165.9 A current, 12.16 V voltage, and 30 CFH gas flow rate produced a weld hardness of 36.4 HRC and an impact toughness of 73.5 J, demonstrating excellent agreement between predicted and experimental results, with SE below 0.04%.the results highlights the effectiveness of integrating RSM and desirability analysis for process optimization, enabling accurate prediction of mechanical responses while reducing experimental complexity. The proposed methodology provides a robust foundation for automated, data-driven control of welding parameters, promoting enhanced weld integrity and sustainable industrial manufacturing practices.
