Optimization of Roughness, Dimensional Conformity, and Porosity of 3D-Printed ASA with MEX: Impact of Critical...

Area of Science:

• Materials Science
• Additive Manufacturing
• Surface Engineering

Background:

• Acrylonitrile-Styrene-Acrylate (ASA) offers high potential for outdoor applications.
• Its use in additive manufacturing (AM) warrants further investigation for optimizing quality characteristics.

Purpose of the Study:

• To determine the optimal 3D printing parameters for ASA to enhance quality metrics.
• To improve surface roughness (Ra, Rq), geometrical accuracy (A2N95), and porosity (PCT).

Main Methods:

• Utilized a Taguchi L25 experimental design to examine six variable control parameters.
• Investigated parameters: extrusion width, raster orientation, layer height, deposition velocity, extruder temperature, and substrate temperature.
• Evaluated reduced quadratic (RQRM), linear (LRM), and quadratic (QRM) regression models.

Main Results:

• Achieved over 250% improvement in surface roughness (Ra, Rq) and 324% enhancement in geometrical accuracy (A2N95).
• Reduced porosity (PCT) by 564% through optimized 3D printing settings.
• Extruder temperature and extrusion width significantly impacted the responses, with RQRM showing high prediction accuracy.

Conclusions:

• Optimized ASA 3D printing settings significantly enhance material quality for demanding applications.
• The reduced quadratic regression model (RQRM) accurately predicts performance, with confirmation runs showing <10% error.
• Findings provide a pathway for utilizing ASA in high-performance 3D printed outdoor components.