Parameter optimization for dimensional accuracy of fused deposition modelling parts

F Gorana, KK Sahu, YK Modi - Materials Today: Proceedings, 2023 - Elsevier
F Gorana, KK Sahu, YK Modi
Materials Today: Proceedings, 2023Elsevier
Abstract Fused Deposition Modeling (FDM), a widely available additive manufacturing (AM)
process, has been gaining popularity among researchers day by day. FDM technique is
capable to fabricate both prototypes and functional parts in variety of materials. For a
particular material, part quality can be enhanced by right combination of the printer
parameters. In this study, parameter optimization of a low cost FDM printer is carried out for
better dimensional accuracy of the fabricated parts. Four process parameters, namely layer …
Abstract
Fused Deposition Modeling (FDM), a widely available additive manufacturing (AM) process, has been gaining popularity among researchers day by day. FDM technique is capable to fabricate both prototypes and functional parts in variety of materials. For a particular material, part quality can be enhanced by right combination of the printer parameters. In this study, parameter optimization of a low cost FDM printer is carried out for better dimensional accuracy of the fabricated parts. Four process parameters, namely layer thickness (LT), build orientation (BO), raster angle (RA) and raster width (RW), each at three levels have been considered to optimize length and diameter of a cuboid shaped Acrylonitrile Butadiene Styrene (ABS) part using Taguchi method. Initially, nine experiments are designed and performed as per the Taguchi’s L9 (34) orthogonal array. Next, signal-to-noise (S/N) ratio is calculated to find the most significant level of the parameters. Finally, analysis of variance is performed to evaluate relative contribution of each parameter for both length and diameter of the fabricated parts. Results reveal that (LT)2 (BO)1 (RA)1 (RW)2 and (LT)1 (BO)3 (RA)3 (RW)2 are the optimal levels of the parameters for length and diameter respectively. Analysis of variance reveals that BO (64.95%) and LT (51.25%) are the most significant parameters for the length and diameter respectively. RA has been second most influencing parameter with 21.45% and 37.13% contribution for length and diameter respectively. RW is found least significant with less than 2% contribution for both length and diameter.
Elsevier
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