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<p>Fused deposition modeling (FDM) builds complex parts by depositing successive layers of material. This study focuses on optimizing 3D printing parameters—including layer thickness, infill pattern, density, print orientation, extrusion temperature and number of contours—to improve the surface roughness (Ra) and printing time of PLA parts. A D-optimal experimental design with five levels per parameter was used, resulting in 40 distinct tests. The results revealed that layer thickness, query print orientation and nozzle temperature had the most significant impact on surface roughness. Higher layer thickness and extreme temperatures (either too low or too high) increased roughness, while the "On-edge" orientation delivered the best surface quality. Printing time was primarily influenced by layer thickness (thicker layers reduced time but worsened surface finish) and infill pattern (simpler patterns were faster). The optimized configuration achieved an Ra of 2.1&#xa0;μm—comparable to the best experimental result (Test 11: 1.05&#xa0;μm) while being 35% faster than the average printing time (45&#xa0;min vs. 69&#xa0;min). It also significantly outperformed the worst-case scenario (Test 20: Ra = 11.85&#xa0;μm, 224&#xa0;min), improving surface quality by 82% and speed by 80%. This demonstrates a well-balanced trade-off between surface finish and efficiency.</p>

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Optimization of Roughness and Productivity in Fused Deposition Modeling: Effects of Printing Parameters on Polylactic Acid Part Performance

  • 期刊论文

  • 发表日期：

    2026年1月9日

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  • Hamza Isksioui,
  • Niama Arreda,
  • Mohamed Bounouib,
  • Abderrahim Oudra,
  • Yassine Elkhouddar,
  • Haj El Moussami

摘要

Fused deposition modeling (FDM) builds complex parts by depositing successive layers of material. This study focuses on optimizing 3D printing parameters—including layer thickness, infill pattern, density, print orientation, extrusion temperature and number of contours—to improve the surface roughness (Ra) and printing time of PLA parts. A D-optimal experimental design with five levels per parameter was used, resulting in 40 distinct tests. The results revealed that layer thickness, query print orientation and nozzle temperature had the most significant impact on surface roughness. Higher layer thickness and extreme temperatures (either too low or too high) increased roughness, while the "On-edge" orientation delivered the best surface quality. Printing time was primarily influenced by layer thickness (thicker layers reduced time but worsened surface finish) and infill pattern (simpler patterns were faster). The optimized configuration achieved an Ra of 2.1 μm—comparable to the best experimental result (Test 11: 1.05 μm) while being 35% faster than the average printing time (45 min vs. 69 min). It also significantly outperformed the worst-case scenario (Test 20: Ra = 11.85 μm, 224 min), improving surface quality by 82% and speed by 80%. This demonstrates a well-balanced trade-off between surface finish and efficiency.