Optimization of process parameter for FDM-3D printed continuous carbon fiber-reinforced PLA composite I-beams

To promote the flexural performance of FDM 3D-printed (fused deposition modeling) continuous carbon fiber-reinforced PLA (Polylactic acid) composite I-beams, a single-factor experiment employing the controlled variable method was first conducted to investigate the influence of individual process parameters—such as printing temperature, speed, layer thickness, and layer spacing—on bending properties. Based on the obtained experimental findings, the optimal three-level settings for four factors were selected as the foundation for subsequent orthogonal experiments. Subsequently, an L9 (3 4 ) (Four-factor, three-level orthogonal experiment) design was employed to optimize FDM-3D printing parameters. Range analysis identified the optimal parameter combination: A1B1C1D2, corresponding to a print spacing of 0.6 mm, print speed of 3 mm/s, print temperature of 220°C, and layer thickness of 0.4 mm. Performance comparison after three-point bending tests revealed that the optimal parameter set with 26 fiber layers significantly enhanced the bending strength of I-beams. Compared to the optimal single-factor combinations for layer thickness, temperature, speed, and spacing, improvements were 18%, 6.7%, 21.8%, and 12.4%, respectively. Compared to the optimal orthogonal set and the worst set, bending strength increased by 9.2% and 48.9%, respectively. Compared to pure PLA, bending strength and modulus increased by 72.2% and 181.6%, respectively. Microstructural analysis further confirmed that the optimized process parameters improved the uniformity of fiber bundle distribution, interfacial adhesion of resin matrix to reinforcing fiber bundles, and the fiber bundle/resin filling effect, thereby enhancing bending performance. This study provides crucial experimental support and design guidance for the engineering application of FDM-3D printed continuous carbon fiber reinforced PLA composite I-beams in small and medium-sized unmanned aerial vehicles.