Multivariate analysis of the mechanical properties of carbon fiber PLA composites using Box-Behnken design

Purpose With the growing global demand for sustainable and high-performance materials in additive manufacturing, particularly for lightweight structural components, optimizing composite formulations is essential. This study aims to investigate how key 3D printing parameters affect the mechanical performance of carbon fiber-reinforced polylactic acid (CFPLA) composites. Design/methodology/approach A Box-Behnken design was applied to evaluate the effects of carbon fiber content, infill percentage and number of wall perimeters on the density, Young’s modulus and specific stiffness of printed specimens. Statistical modeling and multivariate optimization were used to analyze individual and combined factor effects. Findings Carbon fiber content had the greatest influence on Young’s modulus and specific stiffness, while infill and wall count mainly affected density. Specific stiffness was highly responsive to fiber reinforcement and minimally affected by infill. Regression models showed strong predictive power (R2 > 95%). The optimal tested configuration (10% CF, 10% infill, 4 walls) delivered excellent stiffness with a small density increase. CFPLA outperformed pure PLA in stiffness, though at the cost of reduced ductility. This study also suggests that ≈7.5% CF filaments could offer a good balance between performance and manufacturability. Originality/value This work contributes to the global effort to improve structural efficiency in 3D-printed parts by providing a robust experimental framework for optimizing CFPLA composites. The findings offer practical guidance for engineering applications requiring strong, lightweight and sustainable materials.