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Abstract
Material Extrusion (ME), also known as 3D printing, is a widely used additive manufacturing (AM) technique that, among others, employs thermoplastic materials in filaments deposited in a layer-by-layer manner. This study focuses on polylactic acid (PLA) because of its wide use in engineering applications. Although ME provides design flexibility and rapid prototyping, its use in structural engineering is limited by mechanical challenges such as residual stresses, geometric distortions, and potential inter-layer debonding issues. These challenges result from the dynamic thermal profiles experienced during fabrication, including temperature gradients and differential hardening across adjacent layers. Additionally, the rapid heating and cooling cycling of the polymer feedstock amplifies the development of non-uniform internal stresses, which depend on the fabrication settings and the produced object’s geometry. Such effects impair the structural integrity and mechanical performance of the 3D-printed components in applications that require load-bearing capabilities and precise geometries.
This work presents a numerical framework for coupled thermo-mechanical simulations of the ME process using finite element software ABAQUS. A heat transient thermal model computes the temperature distribution during the printing process, which is used as a boundary condition for a subsequent mechanical simulation to predict residual stresses and warpage of the manufactured part, where the physical measurements validate the model warpage predictions. This work investigates the effect of the process parameters (i.e., deposition temperature, heat transfer coefficients) and modeling factors (i.e., meshing and time step strategies) on simulation results. The gathered knowledge is essential for structural engineering as it identifies the limitations of ME in producing structurally reliable components; the developed numerical modeling approach could form the background for the CAD-driven optimization process, employing artificial intelligence (AI) and machine learning (ML) algorithms.
Keywords: fused filament fabrication, finite element method, thermo-mechanical analysis, residual stresses, PLA, fabrication-caused warpage, experimental verification.
