Investigations and optimization of friction stir welding process to improve microstructures of aluminum alloys

• Main Authors: Bazani Shaik, G. Harinath Gowd, B. Durga Prasad
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2019-01-01
• Series: Cogent Engineering
• Subjects: dissimilar welded joints; friction stir welding; grey relational analysis; grey relational grade; multi-responses; optimization
• Online Access: http://dx.doi.org/10.1080/23311916.2019.1616373

This work mainly focus on finding the optimal conditions for improving the efficiency of the dissimilar welded joints that were prepared using the friction stir welding (FSW) process. To carry out further research on the FSW process, it is very important to know the significant process parameters. As per the literature, rotational speed, welding speed, and tilt angle are the most significant parameters and hence have been considered in the current investigation on output responses are tensile strength, impact strength, and elongation are the multi-responses identified; they were also investigated with the help of two-dimensional (2D) plots. The experimental design is planned as per the Taguchi L9 orthogonal array. The straight cylindrical threaded tool is used in this work. AL6082-T651 and AL7075-T651 alloys are taken as the workpiece material based on its applications. The workpieces are cut as per the American Society for Testing and Materials standards. After performing the experiments, each output response is measured at all the welding conditions and is tabulated. This experimental data is used for optimizing the multi-responses using the Taguchi Grey relational analysis (GRA) method. This GRA method helps optimize the multi-responses in an FSW process. In the process of optimization using the GRA method, the signal-to-noise ratios, the Grey relational coefficients, and the Grey relational grades are calculated, and ranking will be given based on the Grey relational grade values. Overall, this method proves suitable for optimizing the multi-responses in the FSW process.