Additive manufacturing (AM) is a process that allows the creation of parts in a single operation by depositing material layer by layer. This not only reduces production time and costs compared to traditional manufacturing methods but also enables the fabrication of customized and complex parts, such as lattice or porous structures. These structures offer advanced properties, like a high strength-to-weight ratio, but are challenging for most conventional manufacturing techniques. AM capabilities allow for free-shape manufacturing, but it's important to note that complex geometries often require support structures to maintain stability during printing. The use of supports requires post-processing, which increases production time and material costs. Even more, it can potentially damage surfaces, compromising their quality and accuracy and limiting design freedom, as post-processing usually requires removing internal supports, which is complicated or impossible, highlighting the need for further research and innovation in this area. For this reason, achieving self-supporting structures for complex shapes with overhanging features or for tailored infill internal structures has become a focus area of research. This work is focussed on lattice members and investigates the influence of factors such as material, subtended angle, and the member diameter on their self-supporting capabilities. Considering the previous parameters, a set of columns was printed using Fused Filament Fabrication (FFF). Dimensional deviations (angle and diameter) plus specimens' shape deviation (straightness and diameter variation) were measured via optical techniques and analysed to quantify their self-supporting capacity. The results were presented by main effect plots and analysed by a non-parametric statistical approach and a factor ranking procedure. We obtained the best results regarding dimensional deviations with overhand angles above 15° and a member diameter of 1.8 mm. On the other hand, straightness is mainly influenced by material density, and the best results were obtained for PolyLactic Acic (PLA).
Robles-Lorite et al. (Sat,) studied this question.