Optimising 3D Printing Parameters through Experimental Techniques and ANOVA-Based Statistical Analysis

Additive manufacturing (AM) has revolutionized the manufacturing industry by enabling the fabrication of complex geometries and designs with ease. 3D printing—fused deposition modeling (FDM) has emerged as a prevalent technique, owing to its versatility and cost-effectiveness. However, the FDM process is complex and depends on multiple parameters, which makes it challenging to obtain high-quality and consistent 3D printed components. The purpose of this study is to simplify the printing process for users and potentially improve the overall quality and consistency of printed objects. This research delved into optimising 3D printing parameters, specifically raster orientation and in-fill speed, for PLA material through three experimental studies. The mean effect of these parameters and the effects of their interaction through analysis of variance (ANOVA) on tensile properties were also discussed. Initial experiments identified the most suitable parameters and its optimal values for PLA, which were then applied to five different materials: PETG, PLA tough, Recycle PLA, Plain PLA, and ABS. Tensile tests assessed the printed parts, and scanning electron microscopy (SEM) was employed to analyze fracture interfaces and material failure causes. This study identified a raster of 45°/−45° and 30 mm/s infill speed as optimal for diverse 3D printing materials. Notably, ABS, PETG, and tough PLA exhibited better tensile strengths, surpassing manufacturer benchmarks. However, Plain PLA and Recycled PLA, despite lower tensile strengths, proved valuable for specific applications. Interestingly, all tested materials showed greater flexibility than manufacturer recommendations, suggesting their suitability in scenarios needing both strength and flexibility. This study's results offer promising avenues for refining 3D printing practices, to the advantage of all users. The findings from this study offer significant insights for future research to investigate the effect of other process parameters on the quality of 3D printed parts, leading to further advancements of AM.