Abstract

Additive manufacturing by Fused Filament Fabrication (FFF) has gained significant attention for producing polymer-based parts, particularly with polylactic acid (PLA). Despite its widespread use, the fatigue performance of FFF-printed PLA components remains difficult to predict due to the complexity of the underlying mechanisms and the strong dependence on processing parameters. This study addresses these challenges through a combined finite element (FE) analysis and inverse parameter identification approach. Using Abaqus and Fe-Safe, fatigue simulations are performed on standardized specimens whose mechanical properties are calibrated from experimental fatigue data through inverse identification techniques. Key parameters such as elastic modulus and fatigue limit are extracted and incorporated into numerical models. The numerical predictions are then validated against available experimental results to assess their accuracy and reliability. Furthermore, a parametric analysis investigates the influence of printing parameters, including layer orientation and infill density, on fatigue behavior. The outcomes of this work provide valuable insights into the fatigue mechanisms of FFF-printed PLA and propose optimization strategies to enhance the durability and reliability of polymer additive manufacturing