| Issue |
E3S Web Conf.
Volume 552, 2024
16th International Conference on Materials Processing and Characterization (ICMPC 2024)
|
|
|---|---|---|
| Article Number | 01034 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202455201034 | |
| Published online | 23 July 2024 | |
Machining Performance Optimization of FSW Using ANN-based PCA - A Hybrid approach for AA6061
Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana
* Corresponding Author: anshu.mit06@gmail.com
In this study, Friction stir welding (FSW) of AA6061 shows the importance of machining parameters such as tool rotational speed (TRS), feed rate (FR) and Tool Pressure angle (TPA). The machining performance has been measured through the ultimate tensile strength (UTS) and Vickers hardness (VH). The Taguchi’s philosophy has been considered in designing the experiment. The machining characteristics were analyzed using the main effect plot and analysis of variance (ANOVA). A principal component analysis (PCA) based composite principal component (CPC) has been used to optimise multi-response. The TRS has been found to be the most significant parameter for obtaining the optimum parameter setting. The performance has been enhanced using ANN technique of the process.
Key words: FSW / AA6061 / UTS / PCA / ANN
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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