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<p>Fused deposition modeling (FDM) is a widely used 3D printing method that produces models’ layer by layer with minimal material waste, making it economical for applications like prosthetics. However, it has drawbacks, including surface roughness and microstructure defects. This study aimed to optimize FDM process parameters to improve surface roughness and microstructure while assessing skin texture using a camera and ImageJ software. The variables investigated in this study include the print speed (40&#xa0;mm/s, 50&#xa0;mm/s, and 60&#xa0;mm/s), layer height (0.1&#xa0;mm, 0.2&#xa0;mm, and 0.3&#xa0;mm), infill density (30 wt.%, 50 wt.%, and 100 wt.%), and nozzle temperature (195&#xa0;°C, 200&#xa0;°C, and 205&#xa0;°C). Samples with flat and curved geometries were printed using polylactic acid (PLA) on an open-source FDM printer. The experiment was designed using an L9 orthogonal array and Taguchi Grey Relational Grade (GRG). Grey relation analysis was used to evaluate the optimal 3D process parameters. Based on GRG, the 3D printing surface roughness and microstructure quality have an optimal 205&#xa0;°C nozzle temperature, 60&#xa0;mm/s printing speed, 0.3 layer height, and 30% infill density. Among parameters, layer height contributed the most (77.69%) to improving surface roughness and microstructure, followed by printing speed (8.59%), infill density (8.41%), and nozzle temperature (5.31%). In the pooling ANOVA for the GRG, the layer height was significant. Skin roughness comparisons showed individuals aged 15–20 have smoother skin (Ra = 1.3&#xa0;µm), while those over 40 exhibit higher roughness (Ra = 5.88&#xa0;µm).</p>

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Optimizing 3D printing process parameters to improve surface quality and investigate the microstructural characteristics of PLA material

  • 期刊论文

  • 发表日期：

    2025年4月21日

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  • Fikadu Mequant Kidie,
  • Tesfa Guadie Ayaliew,
  • Samuel Tesfaye Mekonone

摘要

Fused deposition modeling (FDM) is a widely used 3D printing method that produces models’ layer by layer with minimal material waste, making it economical for applications like prosthetics. However, it has drawbacks, including surface roughness and microstructure defects. This study aimed to optimize FDM process parameters to improve surface roughness and microstructure while assessing skin texture using a camera and ImageJ software. The variables investigated in this study include the print speed (40 mm/s, 50 mm/s, and 60 mm/s), layer height (0.1 mm, 0.2 mm, and 0.3 mm), infill density (30 wt.%, 50 wt.%, and 100 wt.%), and nozzle temperature (195 °C, 200 °C, and 205 °C). Samples with flat and curved geometries were printed using polylactic acid (PLA) on an open-source FDM printer. The experiment was designed using an L9 orthogonal array and Taguchi Grey Relational Grade (GRG). Grey relation analysis was used to evaluate the optimal 3D process parameters. Based on GRG, the 3D printing surface roughness and microstructure quality have an optimal 205 °C nozzle temperature, 60 mm/s printing speed, 0.3 layer height, and 30% infill density. Among parameters, layer height contributed the most (77.69%) to improving surface roughness and microstructure, followed by printing speed (8.59%), infill density (8.41%), and nozzle temperature (5.31%). In the pooling ANOVA for the GRG, the layer height was significant. Skin roughness comparisons showed individuals aged 15–20 have smoother skin (Ra = 1.3 µm), while those over 40 exhibit higher roughness (Ra = 5.88 µm).