Comparative Study of the Sensitivity of PLA, ABS, PEEK, and PETG’s Mechanical Properties to FDM Printing Process Parameters

• Main Authors: Mohammed Algarni, Sami Ghazali
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Crystals
• Subjects: fused deposition modeling; additive manufacturing; ANOVA; mechanical properties; process parameters; PLA
• Online Access: https://www.mdpi.com/2073-4352/11/8/995

Significant advances in fused deposition modeling (FDM), as well as its myriad applications, have led to its growing prominence among additive manufacturing (AM) technologies. When the technology was first developed, it was used for rapid prototyping to examine and analyze a product in the design stage. FDM facilitates rapid production, requires inexpensive tools, and can fabricate complex-shaped parts; it, therefore, became popular and its use widespread. However, various FDM processing parameters have proven to affect the printed part’s mechanical properties to different extents. The values for the printing process parameters are carefully selected based on the part’s application. This study investigates the effects of four process parameters (raster angle, layer thickness, infill percentage, and printing speed) on the mechanical behavior of printed parts that are based on available literature data. These process parameter’s influence on part’s mechanical properties varies depending on the FDM material. The study focuses on four FDM materials: polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), polyether ether ketone (PEEK), and polyethylene terephthalate glycol (PETG). This paper summarizes the state-of-the-art literature to show how sensitive the material’s mechanical properties are to each process parameter. The effect of each parameter on each material was quantified and ranked using analysis of variance (ANOVA). The results show that infill percentage then layer thickness are the most influential process parameter on most of the material’s mechanical properties. In addition, this work identifies gaps in existing studies and highlights opportunities for future research.