Precision control and parameter optimization in screw extrusion 3D printing of polypropylene materials

Abstract

Fused Deposition Modeling (FDM), a widely-utilized additive manufacturing (AM) technology, has found significant favor among automotive manufacturers. Polypropylene (PP) compound is extensively employed in the production of automotive parts due to its superior mechanical properties and formability. However, aiming at the problem of poor dimensional accuracy of pure PP parts, the quality of products can be enhanced by optimizing the combination of processing parameters. In this paper, the dimensional accuracy of 3D-printed components made from pure PP material is investigated. Key influencing factors such as infill percentage, infill pattern, layer thickness, and extrusion temperature are considered. To gain a deeper understanding, fluid simulation is conducted, and mathematical models are established to correlate processing parameters with dimensional accuracy. Furthermore, the Taguchi's experiments are designed and the experimental data are subjected to rigorous Signal-to-Noise ratio and ANOVA analyses. Within the experimental range, the lower extrusion temperature, infill percentage and layer thickness yield the best dimensional accuracy. Considering the influence factors of X, Y and Z directions, the optimal processing parameters for PP prints using screw extrusion 3D printers are determined as follows: an extrusion temperature of 210 °C, an infill percentage of 40 %, a layer thickness of 0.3 mm, and a concentric circle infill pattern. This study provides reference value for the subsequent improvement of the dimensional accuracy of the printed parts.