An investigation of the influence of 3d printing parameters on the tensile strength of PLA material. (2022)

• Record Type: Journal Article
• Authors: Fontana, Luca; Minetola, Paolo; Iuliano, Luca; Rifuggiato, Serena; Khandpur, Mankirat Singh; Stiuso, Vito
• Is Part Of: Materials today. Volume 57:Part 2(2022)
• Page Start: 657
• Page End: 663
• Publication Date: 2022
• Subjects: 3d printing -- PLA -- DOE -- Tensile strength -- Infill -- Makerbot Replicator; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.02.078
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Fused Deposition Modelling (FDM), also known as 3d printing, is one of the most widespread Additive Manufacturing (AM) technologies based on the extrusion of a thermoplastic filament. This layerwise technology allows lightweight products to be built using different infill strategies and percentages. Furthermore, by varying other parameters, such as temperature, printing speed or layer thickness, it is possible to obtain components with different characteristics. Polylactic Acid (PLA) is one of the cheapest and most sustainable materials for 3d printing because it is a biobased and biodegradable plastic. Its use in 3D printing is widely spread among hobbyists and in the communities, such as the ones of Fablabs or the Makers movement. Nevertheless, to reduce the number of uncompliant parts that may fail into operation since they do not meet the expectations of the user, it is important to know in advance the mechanical performance that different 3d printing strategies can ensure for PLA parts. In this paper, Design of Experiment (DOE) is applied to investigate how main 3D printing parameters influence the tensile strength of PLA products. For this purpose, a 3x3 factorial plane with one replication was constructed and used for 3d printing tensile specimens of PLA Tough material using a Makerbot Replicator machine. The tensile test results show that the layer thickness is more significant than the infill percentage for the resistance of PLA products. A regression model is also proposed to allow the user to predict the ultimate tensile strength of PLA products depending on the values of those two parameters.