Optimization of Roughness, Dimensional Conformity, and Porosity of 3D-Printed ASA with MEX: Impact of Critical Process Control Parameters
Dimitrios Sagris, Constantine David, Markos Petousis, Nektarios K. Nasikas, Nikolaos Mountakis, Maria Spyridaki, Nectarios Vidakis
Abstract
High Resolution Image Download MS PowerPoint Slide Acrylonitrile–styrene–acrylate (ASA) is a material with high potential, making it suitable for outdoor applications, which warrants further investigation. Its presence in additive manufacturing (AM) shows potential. Herein, ASA three-dimensional (3D) printed samples are examined using a Taguchi L25 experimental design to achieve optimum quality characteristics, through the improvement of the performance across multiple response metrics, including root-mean-square roughness ( R q ), average roughness ( R a ), actual-to-nominal dimensional deviation (A2N 95 ) and CT scan porosity ( P CT ). Six variable control parameters were examined: extrusion width, raster orientation, layer height, deposition velocity, extruder temperature, and substrate temperature. Experimental findings showed that R a and R q can be improved by more than 250% ( R a reduced from 17.37 to 6.79 μm, R q reduced from 21.71 to 9.29 μm), geometrical accuracy can be enhanced by 324% (A2N 95 reduced from 437.76 134.95 μm), and porosity can be reduced by 564% (PCT reduced from 9.08 to 1.61%) when selecting a proper set of 3D printing settings. Different regression models were evaluated: the reduced quadratic (RQRM), linear (LRM), and quadratic (QRM) regression models. LRM was inferior, while RQRM and QRM had remarkably close prediction accuracies; thus, the RQRM was proposed for this experimental scenario. The two confirmation runs yielded prediction equations with an error of less than 10% between the predicted and calculated values. The extruder temperature and extrusion width were the two parameters causing the greatest impact on the responses.