| Issue |
E3S Web Conf.
Volume 552, 2024
16th International Conference on Materials Processing and Characterization (ICMPC 2024)
|
|
|---|---|---|
| Article Number | 01036 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/e3sconf/202455201036 | |
| Published online | 23 July 2024 | |
Predict the machining performance of FSW of dissimilar material of AI5052 and AZ31 using Multi-Objective Dragonfly Algorithm
Department of Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana.
* Corresponding Author: anshu.mit06@gmail.com
In this study, two dissimilar materials (Al 5052 and AZ31) have been welded using the Friction stir process (FSW). Taguchi’s philosophy has been used to design the experiment using four input parameters (Tool types (TP), Tool traverse speed (TTS), Tool tilt angle (TTA), and Tool rotation Speed (TRS)). The machining performances have been identified using ultimate tensile strength (UTS) and Vickers hardness (HV). The models are evaluated for sufficiency, and then the most significant parameters are determined using analysis of variance (ANOVA). The ANOVA results revealed that TTS has a maximum contribution of 50.2% and 46.5% towards obtaining the high UTS and HV, respectively. The mathematical model using the non-linear model for UTS and HV has been created to predict the mechanical properties of FSWed joints. The prediction welding accuracy of a multi-objective optimization has been performed using the Multi-Objective Dragonfly Algorithm (MODA). The adopted strategy shows a high welding accuracy with minimum computational time.
© 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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