Using 3D Density-Gradient Vectors in Evolutionary Topology Optimization to Find the Build Direction for Additive Manufacturing

Abstract

Given its layer-based nature, additive manufacturing is known as a family of highly capable processes for fabricating complex 3D geometries designed by means of evolutionary topology optimization. However, the required support structures for the overhanging features of these complex geometries can be concerningly wasteful. This article presents an approach for studying the manufacturability of the topology-optimized complex 3D parts required for additive manufacturing and finding the optimum corresponding build direction for the fabrication process. The developed methodology uses the density gradient of the design matrix created during the evolutionary topology optimization of the 3D domains to determine the optimal build orientation for additive manufacturing with the objective of minimizing the need for support structures. Highly satisfactory results are obtained by implementing the developed methodology in analytical and experimental studies, which demonstrate potential additive manufacturing mass savings of 170% of the structure’s weight. The developed methodology can be readily used in a variety of evolutionary topology optimization algorithms to design complex 3D geometries for additive manufacturing technologies with a minimized level of waste due to reducing the need for support structures.