Optimization of PLA/CF 4D printing parameters by Box-Behnben response surface method

Shape memory polymers (SMPs) have the ability to change shape or function in response to external stimuli, which makes them highly valuable for 4D printing applications. Among these, poly(lactic acid) (PLA) has garnered significant attention due to its excellent shape memory properties. Carbon fiber-reinforced PLA (PLA/CF) composites have been widely used because they not only maintain the shape memory effect but also further enhance mechanical properties and dimensional stability. In this study, the effects of key process parameters are systematically investigated for fused deposition modeling (FDM) on the shape memory performance of PLA/CF composites. These parameters include fugitive temperature, number of top/bottom layers, printed layer thickness, degree of bending, fill rate, and printing direction. The investigation was conducted using response surface methodology (RSM) in conjunction with the thermal response mechanism of the PLA/CF material. The shape recovery rate and recovery time were used as evaluation indices. The experimental results indicate that the degree of bending has the most significant impact on the shape recovery rate, while the printing direction has a more pronounced effect on the recovery time. Based on the Box-Behnken Design (BBD) experimental design, a higher-order prediction model was established and optimized to obtain the best combination of process parameters. Validation experiments revealed that the relative errors between the predicted and experimental values of the shape recovery rate and recovery time were 0.97% and 2.47%, respectively. These small errors demonstrate that the constructed model can accurately predict the shape memory properties of PLA/CF samples. This study provides a theoretical basis and methodological reference for optimizing the properties of fiber-reinforced shape memory composites in 4D printing, as well as for the development of a controllable 3D printing process.