Recent advances in multi-axial robotic additive manufacturing have enabled non-planar material deposition, introducing a new design freedom: the shape and sequence of individual layers during fabrication. This has led to the development of Space-Time Topology Optimisation (STTO),
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Recent advances in multi-axial robotic additive manufacturing have enabled non-planar material deposition, introducing a new design freedom: the shape and sequence of individual layers during fabrication. This has led to the development of Space-Time Topology Optimisation (STTO), a method that simultaneously optimises both geometry and deposition sequence to reduce residual stresses and distortions, particularly in Wire-Arc Additive Manufacturing (WAAM). However, the fundamental manufacturing constraints that govern curved-layer deposition remain poorly defined. This thesis investigates and helps define the feasible domain of process and geometric conditions for curved-layer deposition through experimental studies using a robot-assisted additive manufacturing system.
A comprehensive literature review revealed a lack of explicit geometric criteria for printable curved layers, motivating the development of an empirical framework. To explore these constraints, a custom multi-axial robotic printing setup and a two-dimensional toolpath generator were developed, enabling controlled experiments into the geometric limits of non-planar deposition. Results from these experiments show that non-planar deposition is highly sensitive to temporal gradients in material flow rate. Abrupt changes in flow rate disrupt the dynamics of the material extrusion process and lead to defects in the printed parts.
Full-scale tests on optimised models further validated these findings. Despite the identified limitations, the models demonstrated promising manufacturability, as their gradual curvature resulted in relatively consistent flow rates. These results support the practical feasibility of STTO within WAAM and suggest promising directions for future research. Overall, this work advances the understanding of manufacturing limits in non-planar robotic additive manufacturing and helps bridge the gap between computational design and real-world production.