Optimizing the Friction Stir Process Parameters of the AZ31 Mg Alloy/YSZ‐Al₂O₃ Hybrid Surface Composite Using the Response Surface Methodology‐Based Artificial Bee Colony Algorithm

The optimization of friction stir process (FSP) parameters plays a pivotal role in enhancing the mechanical properties of friction‐stirred hybrid surface composites (FSHSC), which are crucial for lightweight and high‐performance structural applications. This study introduces the use of the artificial bee colony algorithm (A_BCA) for optimizing process parameters of yttria‐stabilized zirconia (YSZ) and alumina (Al₂O₃)‐reinforced FSHSC. A three‐factor, five‐level central composite design matrix based on response surface methodology is utilized to develop predictive models for ultimate tensile strength (UTS) and yield strength (YS). Analysis of variance confirms the robustness and reliability of the models, with high statistical significance (p < 0.0001) and R² values of 0.9940 for UTS and 0.9938 for YS. A_BCA identifies optimal parameters—tool rotational speed of 1001.543 rpm, tool transverse speed of 71.896 mm min⁻¹, and tool axial force of 7.23 kN—achieving UTS of 198.345 MPa and YS of 163.534 MPa. The study demonstrates that A_BCA is a powerful tool for optimizing FSP parameters and improving hybrid composite performance. This methodology offers a framework for advancing the mechanical properties of composites, with significant implications for lightweight engineering applications.