Mechanical characterization of Onyx-FR under varying infill Printing Pattern and Orientations, Layer Height, and Extrusion Temperature in FFF Additive Manufacturing
摘要
Fused Filament Fabrication (FFF) is a widely adopted additive manufacturing process that enables the layer-wise fabrication of geometrically complex components. However, the mechanical behaviour of such components is strongly influenced by processing parameters, leading to pronounced anisotropy and variability in material properties. Insufficient understanding of material behaviour under load either necessitates conservative design approaches, increasing material consumption and component mass, or introduces elevated failure risk, that directly affects component’s safety. Developing a systematic and predictive description of the process–structure–property interactions is therefore essential to enable reliable material characterization. This study provides a comprehensive experimental and constitutive investigation of a carbon fiber-reinforced, flame-retardant filament, Onyx-FR, addressing the limited availability of data regarding its process-dependent mechanical behaviour. Quasi-static uniaxial tensile tests were performed in accordance with DIN EN ISO 527 on specimens manufactured under eighteen distinct combinations of print orientation(flat, on-edge, upright), raster angle, layer height, and extrusion temperature. To ensure reliable material characterization, an optimized specimen preparation strategy was implemented to prevent premature specimen’s shoulder failure. The results identify raster angle as the dominant parameter controlling tensile behaviour, while layer height and extrusion temperature exhibit secondary influences. Specimens printed in the on-edge orientation showed a markedly more brittle response than flat-printed specimens, revealing pronounced anisotropy. Based on the observed tensile response, a Ramberg–Osgood-based constitutive model was developed to predict the stress–strain behaviour. The findings establish a robust experimental and analytical foundation for predictive material modelling, enabling safer, more efficient, and performance-driven design of FFF-manufactured components.