A synergistic RSM–simulated annealing metaheuristic framework for predicting and optimizing the tensile strength of 3D-printed high impact polystyrene

Abstract An integrated experimental–computational framework for predicting and optimizing the tensile strength of fused deposition modeling (FDM)-printed high impact polystyrene is presented in this work. The novelty of the study lies in the synergistic integration of response surface methodology based on central composite design (RSM–CCD) with a simulated annealing (SA) metaheuristic algorithm to achieve global optimization of FDM process parameters. Nozzle temperature, print speed, and layer height were systematically investigated to establish their individual and interactive influences on tensile strength. The developed quadratic regression model exhibited high predictive capability with excellent agreement between experimental and predicted responses. To overcome the local-optimum limitations associated with standalone statistical models, the RSM-derived objective function was coupled with the SA algorithm. The hybrid RSM–SA framework identified an optimized parameter combination (250.36 °C, 43.33 mm s −1 , and 0.173 mm) yielding a maximum tensile strength of 27.95 MPa, exceeding all experimental design of experiments conditions. Tensile fractography further revealed a transition from brittle interlayer decohesion in the weakest specimen to pronounced ductile polymer fibrillation in the optimized sample, indicating enhanced interlayer diffusion and reduced defect-assisted failure. The proposed framework demonstrates a robust strategy for improving the mechanical reliability and structural integrity of polymer-based FDM components for engineering applications.