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Review Papers | Welding | India | Volume 12 Issue 8, August 2023
Friction Stir Welding: A Review of Optimization by Taguchi Approach
Neeraj Kumar Gupta | Rakesh Dwivedi [2]
Abstract: The optimization of Friction Stir Welding (FSW) processes has garnered significant interest, driven by the synergy of advanced simulation software and computational power. This review encompasses recent studies that have delved into autonomous optimization methodologies, including Taguchi - based Grey relational analysis coupled with principal component integration, learning - based algorithms such as reinforcement learning and Bayesian optimization. These approaches aim to enhance FSW weld quality by determining optimal parameters, such as rotational speed, plunge depth, dwell time, and welding velocity, with a twofold objective of minimizing defects and maximizing critical factors like failure load and bonded size. Notably, the Taguchi optimization technique has been extensively employed to optimize parameters like rotational and travel speeds, alongside pin shape, showcasing its effectiveness. The interplay of factors like material composition and feed rate further influences the optimization of hardness and tensile strength in the welded joint. Collectively, these endeavors augment joint strength and operational efficiency, underscoring FSW's potential as a pioneering welding technology.
Keywords: Friction Stir Welding, FSW optimization, Taguchi analysis, Weld quality, Process parameters
Edition: Volume 12 Issue 8, August 2023,
Pages: 1162 - 1164