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Comparative Analysis of Fused Deposition Modeling and Digital Light Processing Techniques for Dimensional Accuracy in Clear Aligner Manufacturing.

Wojciech GrzebieluchMagdalena GrajzerKatarzyna Chojnacka
Published in: Medical science monitor : international medical journal of experimental and clinical research (2023)
BACKGROUND This study aimed to compare fused deposition modeling (FDM) and digital light processing (DLP) techniques in terms of dimensional accuracy for printing dental models used for the manufacture of clear dental aligners. MATERIAL AND METHODS Based on the intraoral scan of an adult patient, a sequence of 10 aligner models was created using BlueSkyPlan4. The test models (n=30) were fabricated with 2 desktop 3D printers: (DLP) and (FDM) printers. Two groups of samples were created (digitized using a desktop optical scanner). To calculate trueness (n=20) and precision (n=10), printed models were compared to the source files (REF). REF, DLP, and FDM files were superimposed and converted to point clouds. The cloud-to-cloud distances were calculated using CloudCompare software. Using the same algorithm, distortions of models were measured. Data were analyzed using one-way ANOVA and Tukey's post hoc test. RESULTS Significant differences were found between the trueness and precision of DLP and FDM groups. The average calculated trueness of DLP and FDM was 0.096 mm (0.021) (P<0.001) and 0.063 mm (0.024) (P<0.001), respectively. The average calculated precision of DLP and FDM was 0.027 mm (0.003) (P<0.001) and 0.036 mm (0.003) (P<0.001), respectively. A widening (0.158 mmfor DLP and 0.093 mmfor FDM, P=0.05) and twisting (0.03 mmfor DLP and 0.043 mmfor FDM, P=0.05) of the printed models was observed. CONCLUSIONS Both printers had sufficient precision for aligner models manufacturing. FDM showed a higher trueness and this device can be applied as an alternative to DLP. Polymerization shrinkage is a significant factor in decreasing the trueness of DLP printers.
Keyphrases
  • magnetic resonance imaging
  • high resolution
  • machine learning
  • case report
  • artificial intelligence
  • electronic health record
  • magnetic resonance
  • oral health
  • dual energy