Improving the Surface Roughness, Material Consumption and Abrasion Ability of Additive Manufacturing Products by Segmentation Design

Additive manufacturing technology significantly simplifies the production of complex 3D parts directly by the computer-aided design model. However, additive manufacturing processes have unique flexibility. They still have restrictions that don’t allow engineers to generate some specific geometric shapes, easily. Some of these restrictions are the consumption of materials to supports, the poor abrasion resistance and the inferior surface finish of some surfaces with certain angles. One of the methods to overcome these problems is designing by segmentation. The proposed methodology consists of two steps: 1) segmenting of the 3D model and 2) exploring the best orientation for each segment. In the first step, engineers consider the possible number of segments and the connection method of segments. In this paper, a series of segments is obtained by recognition of features and separating them with one or more appropriate planes. In the second step, the best fabrication orientation should be chosen. The criterion for optimization is that the support volume, abrasion ability, and surface roughness should be minimum. The operation is performed automatically by the algorithm created based on principles of the Particle swarm optimization algorithm using visual C#. Experimental tests show that segmentation design improves additive manufacturing processes from the aspects of material consumption, abrasion volume, and surface quality. This paper presents an original approach to improving the efficiency of additive manufacturing technologies that make the additive manufacturing closer to maturity.