MULTI OPTIMIZATION OF FRICTION STIR WELDING OF ALUMINIUM AA 6061 ALLOY USING TAGUCHI GREY CO RELATION

It is often observed that the parameter tables for machining provided by machine tool manufacturers fail to align with operator requirements and, at times, do not offer efficient guidelines as per the expectations of manufacturing engineers. Therefore, selecting suitable machining parameters is critical for achieving the desired output in any machining process. This study focuses on determining the optimal parametric settings during Friction Stir Welding (FSW) of Aluminium AA 6061 alloy. The process parameters considered include welding speed, axial force, and tool rotational speed, while the quality characteristics studied are tensile strength and tensile elongation. To optimize these parameters, the Taguchi method was employed to design the experiments. An (L9 (3^3)) orthogonal array was selected based on insights from pilot experiments and a thorough literature review. Significant process parameters influencing machining performance were identified using Analysis of Variance (ANOVA) and F-test values in conjunction with experimental results. Verification of the quality improvements achieved using these optimized parameters was performed, and the findings showed enhancements compared to the original setup parameters. Furthermore, linear regression models were developed to establish relationships between machining performance and the selected parameters. In addition to optimizing each parameter individually, multi-response optimization was conducted using Taguchi-Grey relational analysis to consider the combined effects of the process parameters. The results demonstrate an overall improvement in the quality characteristics of FSW for Aluminium AA 6061, validating the effectiveness of the optimized parametric settings.