Relationship between FDM 3D Printing Parameters Study: Parameter Optimization for Lower Defects

Patrich Ferretti, Christian Leon-Cardenas, Gian Maria Santi, Merve Sali, Elisa Ciotti, Leonardo Frizziero, Giampiero Donnici, Alfredo Liverani, Patrich Ferretti, Christian Leon-Cardenas, Gian Maria Santi, Merve Sali, Elisa Ciotti, Leonardo Frizziero, Giampiero Donnici, Alfredo Liverani

Abstract

Technology evolution and wide research attention on 3D printing efficiency and processes have given the prompt need to reach an understanding about each technique's prowess to deliver superior quality levels whilst showing an economical and process viability to become mainstream. Studies in the field have struggled to predict the singularities that arise during most Fused Deposition Modeling (FDM) practices; therefore, diverse individual description of the parameters have been performed, but a relationship study between them has not yet assessed. The proposed study lays the main defects caused by a selection of printing parameters which might vary layer slicing, then influencing the defect rate. Subsequently, the chosen technique for optimization is presented, with evidence of its application viability that suggests that a quality advance would be gathered with such. The results would help in making the FDM process become a reliable process that could also be used for industry manufacturing besides prototyping purposes.

Keywords: defects; optimization; optimized FDM; printing parameters; void occurrence.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Defect appearance on a PLA specimen: (a) material voids between adjacent lines.
Figure 2
Figure 2
Nozzle length difference according to (a) lower volumetric flow rate, (b) higher volumetric flow rate.
Figure 3
Figure 3
Printing line geometry characterization.
Figure 4
Figure 4
Defects (A,B).
Figure 5
Figure 5
Defect (C).
Figure 6
Figure 6
Defect (D).
Figure 7
Figure 7
Example of a printing gcode (left); last 8 lines of gcode drawn in geogebra (right); in red: the extrusion moving path, in gray: the shift movement of a single printer head.
Figure 8
Figure 8
Influence of the number of shell (contour) lines on 30 × 30 × 30 mm cube, nozzle 0.4 mm, line width 0.4 mm, layer height 0.15 mm, raster angle 45°.
Figure 9
Figure 9
Lower extrusion width (on top) and higher extrusion width (on bottom) compared for a given dimension L.
Figure 10
Figure 10
Influence of width (considering 2 shell (contour) lines, raster angle 45°, nozzle 0.4 mm, layer height 0.15 mm).
Figure 11
Figure 11
Different nozzle diameter compared at different layer heights; the width is equal to nozzle diameter for each of those.
Figure 12
Figure 12
Influence of geometric dimension on volume of defects, layer height 0.15 mm, width 0.4 mm, 2 shell (contour) lines, raster angle 45°.
Figure 13
Figure 13
Comparison on the influences of the geometry considering the 0.4 mm and 0.6 mm nozzle; in the case of a 0.4 mm nozzle, the layer height is 0.15 mm, width 0.4 mm; in the case of a 0.6 mm nozzle, the layer height is 0.2 mm and width 0.6 mm.
Figure 14
Figure 14
Flow chart of the optimization process.
Figure 15
Figure 15
Optimization process loop cycle.
Figure 16
Figure 16
Printing quality on the microscope (20×): (a) not optimized; (b) increasing performance; and (c) fully optimized.

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Source: PubMed

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