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The goal of this research is to develop and verify an algorithm to predict the fill density of 3D printed cylindrical constructs as a function of critical slicing parameters. Open-source 3D printing is being applied to the pharmaceutical and biomedical domains where characteristics including drug release rate and compressive strength depend on fill density. Understanding how slicing parameters affect fill density in the printed construct is important to appropriately tailor these characteristics. In this study, we evaluated the relationship between slicing fill density (SFD), extrusion width (EW), layer height (LH), construct diameter and measured fill density (MFD). The developed algorithm provides novel insight into the effects of interconnects and rasters on the distribution of intra-matrix material. We analyze 27 combinations involving 3 levels of EW (0.40, 0.44, 0.48 mm), SFD (15, 25, 35%) and LH (0.15, 0.20, 0.25 mm). The SFD is smaller than and deviates from MFD with a maximum error of 18.62% and from predicted fill density (PFD) with a maximum error of 19.50% compared to the maximum error of 4.30% between PFD and MFD. The predicted interconnect contribution and error reduce with increasing SFD and cylinder diameter but are more prominent at lower values. Our work highlights the perils of employing open-source 3D printing without a sound understanding of the underlying parametric relationships. The proposed predictive model could be used in conjunction with Slic3r, an open-source slicing software, to predict fill density to a reasonable degree of accuracy (less than 5% error) for relatively smaller cylindrical constructs.

Effects of slicing parameters on measured fill density for 3D printing of precision cylindrical constructs using Slic3r