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Research Article

Friction stir-welding of AZ31B Mg and 6061-T6 Al alloys optimization using Box-Behnken design (BBD) and Artificial Neural network (ANN)

Dame Alemayehu Efa1, Endalkachew Mosisa Gutema1, Hirpa G. Lemu2, Mahesh Gopal1

1Dept. of Mechanical Eng., College of Eng. and Technology, Wollega University, Nekemte, Ethiopia
2Dept. of Mechanical and Structural Eng. and Materials Science, Faculty of Science and Technology, University of Stavanger, N-4036 Stavanger, Norway

Keywords

Abstract


Box-Behnken Design; 

Response Surface Methodology;

Friction Stir-Welding;

COMSOL Multiphysics® 6.0 Software;

Artificial Neural Network;

Peak Temperature

The primary goal of the study is to optimize the welding parameters using Friction Stir Welding (FSW) to join AZ31B Mg and AA 6061 alloys considering input parameters such as rotational speed, welding speed, shoulder-to-pin diameter ratio and plunge force and output parameters as peak temperature. The simulation experiment is carried out using COMSOL Multiphysics® 6.0 Software. The simulation experiment is designed using the Box-Behnken design (BBD) of Response Surface Methodology (RSM) and mathematical models were developed.  The Analysis of Variance (ANOVA) is used to assess the features of the performance effectiveness of the parameters. Both direct and indirect interaction effects are investigated; the results indicate that the rotational speed is the most influential parameter when compared to other factors; as rotational speed increases consequently; there is an increase in temperature. Finally, the Artificial Neural Network was trained and tested in MATLAB software to optimize the parameters. The validation was performed to predict the minimal predicted temperature value. The confirmatory tests reveal that the predicted results are extremely close to the experimental values from the simulation.

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2023 Reviewer Awards:

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2023 Best Paper Award:

The paper authored by Ferzan Fidan, Naim Aslan, Mümin Mehmet Koç entitled as “Morpho-structural and compressive mechanical properties of graphene oxide reinforced hydroxyapatite scaffolds for bone tissue applications” is awarded.



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The paper authored by Ercan Işık, Ehsan Harirchian, Hüseyin Bilgin, Kirti Jadhav entitled as “The effect of material strength and discontinuity in RC structures according to different site-specific design spectra" is awarded.


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