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

Abstract

Abstract In order to improve the strength and surface quality of fiber-reinforced composite 3D printed parts and reduce the overfilling and underfilling caused by the manufacturing process of molten filaments under continuous paths, a co-extrusion control and optimization method based on matrix adaptive feeding with printing speed and deposition spacing is proposed in this paper. The method not only achieves surface void filling under different paths, but also reduces the porosity of the printed parts and improves the strength of the printed parts by adjusting the matrix extrusion under different deposition spacings. Compared with the common co-extruded model, the tensile strength is increased by 18% , the bending strength is increased by 23.4% and the porosity decreased by 54.4%. The proposed method is applicable to models with arbitrary continuous infill patterns and improves the quality of fiber-reinforced printed parts, especially to avoid structural failure due to uneven filling.