| publication name | Optimization of friction stir welding of AA6082-T6 parameters using analysis of variance and grey relational analysis |
|---|---|
| Authors | Noah E El-Zathry, Ashraf I Hassan, Ahmed A El-Betar, Ibrahim Sabry |
| year | 2022 |
| keywords | FSW; GRA: ANOVA |
| journal | 20th INTERNATIONAL CONFERENCE ON APPLIED MECHANICS AND MECHANICAL ENGINEERING (AMME) |
| volume | Not Available |
| issue | Not Available |
| pages | Not Available |
| publisher | Not Available |
| Local/International | Local |
| Paper Link | Not Available |
| Full paper | download |
| Supplementary materials | Noah E. El-Zathry_Optimization of friction stir welding of AA6082-T6 parameters using analysis of variance and grey relational analysis.pdf |
Abstract
Friction stir welding (FSW) is a solid-state welding process, which plays a significant role in solid-state welding processes for nonferrous alloys. Conventional arc welding processes for aluminum alloys such as tungsten inert gas (TIG) and metal inert gas (MIG) are replaced by FSW. The effect of process parameters such as tool rotational and traverse speeds, tool geometry, plunge depth, tilt angle, etc., on weld quality were considered in several optimization studies. Multi-criteria decision-making (MDCM) techniques such as grey relational analysis (GRA) were used to determine the optimal condition among experimental runs designed using response surface methodology (RSM). The Taguchi method was widely applied with MCDM techniques. Therefore, the experiments were conducted according to response surface methodology. Input parameters were (14, 16 and 18) mm for shoulder diameter (SD), (0.0, 0.2 and 0.4) mm for plunge depth (PD), and (30, 60 and 90) mm for fixture position (FP), which is the distance between fixture bolts used to fix the welded plate. The results obtained by GRA were similar to the ANOVA optimizer, and the optimum process conditions are shoulder diameter of 14 mm, plunge depth of 0.2 mm, and fixture position of 60 mm.