Mechanism-driven process planning for continuous fiber-reinforced suspension lattice structures with complex path features via self-supporting suspension printing

Abstract

Continuous fiber-reinforced polymer additive manufacturing (CFRP-AM) enables the creation of a novel class of composite structures known as suspension lattices, formed by stacking distinct layer patterns via self-supporting suspension printing (SSSP). With hybrid topologies and complex internal channels, these structures open new avenues for structural enhancement and multifunctional integration. However, engineering suspension lattices with intricate corner path features remains challenging due to limited understanding of printing mechanisms and a lack of effective process planning methods to address manufacturing issues, like gravity-induced sagging and fiber-tension-induced turning slippage. This study proposes a mechanism-driven process planning method for architecting geometrically accurate and mechanically robust suspension lattices. The process is categorized into two phases (i.e., fabrication of primary skeletons and secondary elements) to decouple the structural complexity. The underlying printing mechanism is revealed through experimental characterization of diverse path features, which facilitates the development of physics-informed few-shot learning (PI-FSL) models for accurate prediction of printing quality. A slip transmission mechanism for sequential corner features is introduced that leverages PI-FSL models to quantify the influence of preceding path slippage on the subsequent path accuracy. Subsequently, these models are integrated with a genetic algorithm for path planning of suspension lattices. The proposed approach achieves high efficiency in three complex target patterns, as evidenced by desirable path accuracy with geometric deviations of less than 1.0 mm. Furthermore, the effectiveness of this method is demonstrated through two potential applications in creating two-and-a-half-dimensional (2.5D) lattices for battery enclosures and three-dimensional (3D) skeletons for drone protective cages.