A Review on the Existing Intelligent Techniques for Simulation, Modeling, and Optimization of Friction Stir Welding

Authors

  • Sipokazi Mabuwa Department of Mechanical Engineering, College of Science, Technology, and Engineering, Florida Campus, University of South Africa, 28 Pioneer Ave, Florida Park, Roodepoort, 1709, South Africa
  • Velaphi Msomi Department of Mechanical Engineering, College of Science, Technology, and Engineering, Florida Campus, University of South Africa, 28 Pioneer Ave, Florida Park, Roodepoort, 1709, South Africa https://orcid.org/0000-0003-3773-8538
  • Oritonda Muribwatoho Department of Mechanical Engineering, Durban University of Technology, P.O. Box 1334, Durban, 4000, South Africa
Volume: 15 | Issue: 4 | Pages: 25318-25326 | August 2025 | https://doi.org/10.48084/etasr.10212

Received: 12 January 2025 | Revised: 16 February 2025 | Accepted: 6 March 2025 | Online: 2 August 2025


Corresponding author: Sipokazi Mabuwa

Abstract

Friction Stir Welding (FSW) is a joining technique mostly used in aluminum alloys. The process includes multiple factors and control parameters, optimizing the quality of welds, enhancing efficiency, and reducing defects. This study examines different approaches used in FSW, such as the Taguchi method, Response Surface Methodology (RSM), Factorial Design (FD), numerical simulations and computational models, like Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Artificial Neural Networks (ANN), and Genetic Algorithms (GA). The study also proposes the development of advanced simulation models and the integration of Artificial Intelligence (AI) for real-time process control.

Keywords:

Friction Stir Welding (FSW), optimization, weld quality, Taguchi method, Response Surface Methodology (RSM), Factorial Design (FD)

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[1]
S. Mabuwa, V. Msomi, and O. Muribwatoho, “A Review on the Existing Intelligent Techniques for Simulation, Modeling, and Optimization of Friction Stir Welding”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 4, pp. 25318–25326, Aug. 2025.

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