Abstract
The advent of material technology witnessed an enormous application of aluminium alloys in day-to-day life. The Aluminum Alloy 6061 is one such alloy that finds immense application in engineering field. However, joining process of such aluminium alloys is difficult task through conventional techniques due to occurrence of high thermal conductivity. Friction stir welding (FSW) turns out to be an innovative welding technique used for joining such alloys and comparatively less hazard. The FSW process required to controlled several working parameters for strengthen the mechanical properties. It becomes very important to optimize these process parameters to obtain a good weld with enhanced mechanical properties. The current article describes the experimental procedure for welding AA6061 alloy at different operating parameters. Taguchi method and regression analysis which is widely acceptable methodology implemented to optimize different FSW parameters using L16 orthogonal array. The present study implemented the ANOVA table to examine the influence of tool geometry, rotational speed and welding speed on tensile strength, percentage elongation and harness respectively. The percent contributions of factors i.e., tool geometry, rotation speed and welding speed to the tensile strength is found to be of 33.4%, 4.69% and 58.39% respectively. It is observed that welding speed (58.39%) plays significant role influencing the tensile strength. Similarly, the percentage contributions of tool geometry, rotation speed and welding speed on percentage elongation is found to be 35.08%, 14.29% and 38.28% respectively. The observation concluded that welding speed is the most influential factor for percentage elongation. In addition, the percent contributions of the tool geometry, rotation speed and welding speed on hardness reported as 50.1%, 19.36% and 20.49% respectively. This concluded that tool geometry is the most effective factor for hardness. The predicted results are validated with experimental data's depicted a good convergence with optimization techniques for controlled operating parameters.