GrowFill (2024-11)¶

Additive Manufacturing (AM) has been widely applied in different fields to facilitate the fabrication of intricate geometries and advanced material strategies. Notably, Large Format Additive Manufacturing (LFAM) has seen substantial growth in the architectural field, offering extended opportunities for customized living spaces. However, existing infill generation strategies and toolpath planning methods developed for small-scale 3D printing fall short in meeting the emerging demands of LFAM. LFAM demands optimized, high-quality toolpaths to ensure smooth and even printing. Simultaneously, there is a pressing need to reduce material usage to enhance efficiency. Addressing these challenges, this research proposes an innovative method named GrowFill that seamlessly integrates infill generation and toolpath planning. This method not only produces continuous and smooth toolpaths but also adjusts infill densities based on structural requirements, significantly minimizing material consumption. This system utilizes the Topology Optimization algorithm (TO) to dictate the most efficient material distribution to guide the propagation process of a space-filling algorithm, Differential growth (DG), to produce adaptive infill. Practical applications, including prototype tests with PLA and clay, demonstrate the effectiveness of this approach in creating efficient and high-quality prints.