An adaptive matrix material extrusion optimization model for in situ impregnated continuous fiber-reinforced 3D printing

Microscopic porosity is an important cause of structural failure in 3D printing of continuous fiber reinforced polymer. To reduce the overfilling and underfilling caused during the fabrication of the molten filament under a continuous path and avoid microscopic porosity, this study proposes an adaptive co-extrusion control and optimization model to achieve uniform filling of the matrix material by dynamic adjustment. This optimization process first models the mixture ratio of the matrix material and reinforcing material using an online prepreg co-extrusion fiber filament fabrication process and then constructs a dynamic adjustment factor by analyzing the geometry of the deposition path. The dynamic extrusion volume adjustment model takes the tool path and outputs the optimized process code; therefore, it can be adapted as a post-process for similar 3D printing slicing and path planning procedures. Compared with the co-extruded model that is not optimized for matrix adaptive adjustment, the tensile and flexural strengths increased by 18% and 23.4%, respectively. The porosity decreased by 54.4%. In particular, structural failure owing to uneven filling of fiber-reinforced printed parts is avoided.