Automatic Shape Modification for Self-Supporting Structures in Additive Manufacturing

Abstract Additive manufacturing (AM) is a class of advanced manufacturing technologies that facilitates fabrication of geometrically complex, high-performance functional parts. AM processes often produce a “near-net” shape comprising the intended design and sacrificial support structures to be removed in postprocessing. The amount of extra material in the near-net shape directly increases fabrication cost and clean-up time. This paper presents a shape modification method for AM parts to minimize the need for sacrificial material in the near-net shape. Given an existing triangulated boundary representation of the part, we formulate the problem as a generic shape optimization that minimizes the changes made to the original geometry by locally modifying vertex coordinates while both maintaining the manifold nature of the representation and satisfying the overhang angle constraints, when possible. Specifically, we augment a pseudo-energy regularization term to our primary objective function for self-supporting to ensure that the optimized shape is valid and suitable for AM. We propose two mesh regularization methods, using virtual springs and sphere packing, and provide differentiable expressions of the objective function and constraints to enable efficient gradient-based optimization. We show that the sphere packing is more robust and retains the quality of the mesh during optimization. Finally, we demonstrate the effectiveness and efficiency of our method in modifying realistic models in 3D.