MULTI RESPONSE OPTIMIZATION OF SUBMERGED FRICTION STIR WELDING PROCESS PARAMETERS USING GREY RELATIONAL ANALYSIS

Friction stir welding (FSW) invented by TWI is a solidstate joining process, which is used to weld high-strength aluminum alloys and other metallic alloys which are non weldable by conventional fusion welding process. In this work, AA6063-0 alloy of 150 mm in length, 75 mm in width and 6mm thickness is taken and friction stir welded in submerged condition in order to improve the joint properties. The chosen process parameters are tool pin profiles (cylindrical, threaded and tapered), rotational speed and welding speed. The process parameters are optimized with multi response characteristics including hardness and average grain size at the nugget zone. The traditional Taguchi approach is insufficient to solve a multi response optimization problem. Therefore, Grey Relational Analysis (GRA) is used in this current work. The optimal result indicates that the multi response characteristics of the AA6063 0 during the submerged friction stir welding process can be enhanced through Grey Relational Analysis. In order to investigate the significance of process parameters, Analysis of Variance (ANOVA) is carried out. The mechanical properties and microstructure variation of both the normal FSW and submerged FSW joints are compared.