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<p>Material extrusion (ME) is a globally recognized additive manufacturing (AM) technique for fabricating custom-designed thermoplastic and fiber-reinforced polymer (FRP), delivering budget-friendly, rapid, and efficient use of material. However, the substantial drawbacks faced with the printed items were weaker mechanical performance and surface texture. Effective selection of variables greatly enhances both surface smoothness and mechanical attributes. This research aims to enhance the tensile strength (TS), shore D hardness (SDH), and surface roughness (SR) of polylactic acid (PLA). Experimentation based on three levels set up and multi-target optimization was conducted utilizing Taguchi L<sub>9</sub> orthogonal array and grey relational analysis (GRA), respectively. The result demonstrates that the optimized variables for output responses vary according to the specific printing factor and targeted outcomes. Nozzle temperature, layer thickness, and print rate are found to be the key factors influencing the resulting parameters. The optimized control parameters noted for multi-goal optimization are: 208&#xa0;°C—extruder temperature, 0.18&#xa0;mm—layer thickness, 45&#xa0;mm/s—print speed, and 22.5°—raster angle. Multi-target optimization enabled a significant reduction in the trade-off between surface texture and mechanical performance. Optimized printing parameter setup improves mechanical characteristics and surface appearance of 3D-printed end items, unlocking greater potential for the 3D printing industry.</p>

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Multi-criteria optimization of 3D printing parameters for polylactic acid (PLA)

  • 期刊论文

  • 发表日期：

    2025年8月20日

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  • Mohd Yousuf Ali Ali,
  • G. Krishna Mohana Rao,
  • B. Anjanaeya Prasad

摘要

Material extrusion (ME) is a globally recognized additive manufacturing (AM) technique for fabricating custom-designed thermoplastic and fiber-reinforced polymer (FRP), delivering budget-friendly, rapid, and efficient use of material. However, the substantial drawbacks faced with the printed items were weaker mechanical performance and surface texture. Effective selection of variables greatly enhances both surface smoothness and mechanical attributes. This research aims to enhance the tensile strength (TS), shore D hardness (SDH), and surface roughness (SR) of polylactic acid (PLA). Experimentation based on three levels set up and multi-target optimization was conducted utilizing Taguchi L9 orthogonal array and grey relational analysis (GRA), respectively. The result demonstrates that the optimized variables for output responses vary according to the specific printing factor and targeted outcomes. Nozzle temperature, layer thickness, and print rate are found to be the key factors influencing the resulting parameters. The optimized control parameters noted for multi-goal optimization are: 208 °C—extruder temperature, 0.18 mm—layer thickness, 45 mm/s—print speed, and 22.5°—raster angle. Multi-target optimization enabled a significant reduction in the trade-off between surface texture and mechanical performance. Optimized printing parameter setup improves mechanical characteristics and surface appearance of 3D-printed end items, unlocking greater potential for the 3D printing industry.