This work is focused on the influence of different friction stir welding (FSW) parameters on AA6082 T-6 and AA5083-O alloys welding quality, by using Taguchi, Grey Relational and Weight Method. Four welding parameters were investigated, namely tool rotation speed (TRS), welding speed (WS), tool pin profile (TPP) and shoulder diameter (SD). | Dissimilar alloys AA6082 AA5083 joining by FSW and parametric optimization using Taguchi grey relational and weight method Engineering Solid Mechanics 2018 51-66 Contents lists available at GrowingScience Engineering Solid Mechanics homepage esm Dissimilar alloys AA6082 AA5083 joining by FSW and parametric optimization using Taguchi grey relational and weight method Sumit Jaina Neeraj Sharmab and Rajat Guptac a Mechanical and Automation Engineering HMR of Institute of Technology and Management Hamidpur New Delhi-110036 India b Department of Mechanical Engineering Maharishi Markandeshwar University Mullana Haryana-133207 India c Department of Mechanical Engineering . Inderaprastha Institute of Technology Karnal Haryana-132001 India A R T I C L EI N F O ABSTRACT Article history This work is focused on the influence of different friction stir welding FSW parameters on Received 26 June 2017 AA6082 T-6 and AA5083-O alloys welding quality by using Taguchi Grey Relational and Accepted 22 October 2017 Weight Method. Four welding parameters were investigated namely tool rotation speed TRS Available online welding speed WS tool pin profile TPP and shoulder diameter SD . The optimized setting 23 October 2017 Keywords of these input parameters was investigated so that weld parts quality could be optimized. AA5083-O Analysis of variance ANOVA was used to investigate the effects of these welding process AA6082 T-6 parameters on response variables viz. elongation EL and ultimate tensile strength UTS . Dissimilar alloys joining Single response optimization was carried using Taguchi Technique while grey relational FSW analysis GRA was used for simultaneous optimization of two responses. Once the optimal GRA settings of control factors were identified confirmation experiments were performed for the Taguchi validation of results. In the multi-response optimization TRS was found to have the maximum Weight method effect followed by WS SD and TPP. Weight
