A Topology Optimization Approach to the Support Structure Problem in Additive Manufacturing

Additive manufacturing encompasses all technologies that produce three-dimensional objects, usually by adding one layer of material at the time. Technologies have been developed for a wide range of materials, including metal, thermoplastics, ceramics, composites and glass. While additive manufacturing has the potential to produce very complex geometries, it is still characterized by certain technological constraints. One of these constraints is the need for a temporary support structure. Depending on the additive manufacturing technique used, the support structure is required to ensure a component can resist gravity, to avoid excessive thermal deformations and/or to improve the heat dissipation during manufacturing. In current practice, the support structure needed to print a component is designed manually based on heuristic rules and engineering judgement. As printing and removing the support structure is a time and material consuming process, the efficiency of the additive manufacturing process can be improved by reducing or eliminating the amount of support structure needed. This thesis explores how topology optimization can be used to reduce or eliminate the required amount of support structure in additive manufacturing. Two approaches are described to achieve this goal. The first approach focusses on redesigning the component such that it becomes self-supporting, so eliminating the need for additional support structure. More specifically, the focus is on the effect of gravity. Due to gravity, the maximum overhang angle that can be printed without support is limited. In the literature, various methods for topology optimization including overhang angle control have been proposed. However, none of these methods takes the minimum printable feature size (or length scale) into account, sometimes resulting in very thin structures that cannot be manufactured. In this thesis, a new filtering scheme is proposed that accounts for both the maximum overhang angle and the minimum length scale in a minimum compliance topology optimization problem. The second approach addresses the optimal design of support structure for a given component. Here, the focus is on inhibiting large thermal deformations in metal-based additive manufacturing. A lattice-type support structure is considered, which is modeled as a homogenized material for which the stiffness properties are given by a simple surrogate model. The inherent strain method is adopted to simulate the thermal deformations of the printed part. These ingredients are used in a topology optimization framework that is capable of automatically generating an optimized support structure taking into account the maximum allowable displacement. Both approaches are applied to a 2D and a 3D example. Results of the first approach show that the developed filtering scheme successfully reduces the required volume of support structure by providing length scale and overhang control to the optimization process. The second approach results in a significant reduction of the required volume of support structure needed to limit the vertical displacements to the maximum allowable value. The research will be done under the supervision of Mattias Schevenels and Geert Lombaert at the department of Architecture; Faculty of Engineering Science of the KU Leuven.status: publishe