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

Öz

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.

Anahtar Kelimeler

• FFF
• FDM
• Taguchi
• Design of Experiments
• Grey Relational Analysis
• MEX

Kaynakça

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