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Dergiler / International Journal of 3D Printing Technologies and Digital Industry / 2026 / Cilt: 10 Sayı: 1

3D PRINTER PARAMETER OPTIMISATION FOR PLA USING TAGUCHI AND GREY RELATIONAL ANALYSIS METHODS

Gayenur Akyüz(ONDOKUZ MAYIS UNIVERSITY, FACULTY OF ENGINEERING)0009-0005-1428-5662
Zeynep Ertekin(ONDOKUZ MAYIS ÜNİVERSİTESİ)0009-0005-4073-2307
Hasan Baş(ONDOKUZ MAYIS UNIVERSITY, FACULTY OF ENGINEERING)0000-0002-5653-3813
Sayfa
234–242
Yayın Tarihi
2026-04-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Adopting the methodology used in the study of industrial applications aims to obtain the most optimal dimensions, improve production quality, and contribute to the broader use of FFF technology.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:This study aims to increase measurement accuracy and print quality by using Fused Filament Fabrication (FFF or Fused Deposition Modeling (FDM)) and to examine the effect of parameters that cause variability.
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Temel Bulgular & Veri:A total of 25 samples were produced at five different levels for each factor using Grey Relational Analysis and Taguchi Design of Experiments.
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Sonuç & Katkı:Adopting the methodology used in the study of industrial applications aims to obtain the most optimal dimensions, improve production quality, and contribute to the broader use of FFF technology.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:25 samples
⚙️Değişkenler:FFF · FDM · Taguchi

Özet

This study aims to increase measurement accuracy and print quality by using Fused Filament Fabrication (FFF or Fused Deposition Modeling (FDM)) and to examine the effect of parameters that cause variability. In this context, PLA (Polylactic Acid) filament was used, and printing parameters such as printing temperature, printing speed, layer thickness, fan speed, printing speed (outlines), and roof thickness were optimized with Grey Relational Analysis and Taguchi Design of Experiments. A total of 25 samples were produced at five different levels for each factor using Grey Relational Analysis and Taguchi Design of Experiments. The samples were evaluated using the intuitive quality scoring method, each scoring between 1 and 10. As a result of the research, we determined 215 °C printing temperature, 100 mm/s printing speed, 0.15 mm layer thickness, 90 mm/s fan speed, 15 mm printing speed (outlines), and 0.8 mm roof layer thickness as optimal printing parameters. This research aims to determine the effect of the production parameters on the measurement accuracy of parts produced by the FFF method and the values at which these parameters should be based on the overall quality analysis. Adopting the methodology used in the study of industrial applications aims to obtain the most optimal dimensions, improve production quality, and contribute to the broader use of FFF technology.

Abstract

This study aims to increase measurement accuracy and print quality by using Fused Filament Fabrication (FFF or Fused Deposition Modeling (FDM)) and to examine the effect of parameters that cause variability. In this context, PLA (Polylactic Acid) filament was used, and printing parameters such as printing temperature, printing speed, layer thickness, fan speed, printing speed (outlines), and roof thickness were optimized with Grey Relational Analysis and Taguchi Design of Experiments. A total of 25 samples were produced at five different levels for each factor using Grey Relational Analysis and Taguchi Design of Experiments. The samples were evaluated using the intuitive quality scoring method, each scoring between 1 and 10. As a result of the research, we determined 215 °C printing temperature, 100 mm/s printing speed, 0.15 mm layer thickness, 90 mm/s fan speed, 15 mm printing speed (outlines), and 0.8 mm roof layer thickness as optimal printing parameters. This research aims to determine the effect of the production parameters on the measurement accuracy of parts produced by the FFF method and the values at which these parameters should be based on the overall quality analysis. Adopting the methodology used in the study of industrial applications aims to obtain the most optimal dimensions, improve production quality, and contribute to the broader use of FFF technology.

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Bu Makaleye Atıf Yap

Akyüz, G., Ertekin, Z., Baş, H. (2026). 3D PRINTER PARAMETER OPTIMISATION FOR PLA USING TAGUCHI AND GREY RELATIONAL ANALYSIS METHODS. International Journal of 3D Printing Technologies and Digital Industry, Cilt: 10 Sayı: 1, 234–242. https://doi.org/10.46519/ij3dptdi.1695523

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Kaynakça (22)

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