<![CDATA[The development of fused deposition modelling (FDM) 3D printer models is increasing where the applications can be found in several aspects such as rapid prototyping, functionally components, and parts for assembly process. These conditions required excellent printing quality. One of the factors that affect the printing quality was process parameter setting. There are several parameters process that are used in 3D printing. Hence, the use of these parameters that recommended by manufacturer often give the average results, not the best results. The recent study purposes are to gain optimal setting that give accuracy in the dimension and suitable surface condition. There are 12 factors with 3 different levels. The study used Taguchi method L-27 and grey relational analysis (GRA) to determine the most efficient combinations that can fulfill multi-objective. The results showed that to acquire the accuracy and total dimension, the following combination are used; LH0,075mm, LW0,45mm, IPLines, WT0,8mm, PT205C, FR85%, RD6,5mm, RS30mm/s, PS30mm/s, OWS15mm/s2, PA10mm/s2, and PJ10mm/s where wall thickness (WT); flow rate (FR); and retraction distance (RD) used as 3 essential factors that can influence the respond of the machine. The best surface roughness gathered with the combination as follow; LH0,075mm, LW0,35mm, IPGrid, WT0,8mm, PT200C, FR95%, RD2mm, RS30mm/s, PS70mm/s, OWS25mm/s, PA3000mm/s2, dan PJ30mm/s where the layer height (LH) was the essential factor that affect the machine respond. The accuracy of the dimension and the most optimum surface roughness can be acquired by the following combinations: LH0,075mm, LW0,35mm, IPGrid, WT0,8mm, PT205C, FR95%, RD4,5mm, RS30mm/s, PS70 m/s, OWS15 mm/s, PA3000 mm/s2, dan PJ10mm/s. ]]>
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