Evaluation of the Efficiency of Products Packing in Additive Machine Workspace Based on Fractal Analysis

The research results presented focus on the possibility of assessing the utilization of additive machine workspace through fractal analysis. This assessment enables a comparative analysis of the algorithm's effectiveness in placing 3D models of products within the workspace, considering essential criteria such as the uniformity of product material distribution. Apart from the primary optimization criteria, achieving an even distribution of product material within the workspace is crucial when packing products. This requirement holds particular significance for additive methods such as SLS, SLM and SLA. Fractal analysis of the working space of an additive machine was conducted by initially dividing it into subspaces. A statistical analysis of fractal dimensions obtained for various subspace sizes was then utilized to quantitatively assess the characteristics of filling the workspace with product models. The resulting fractal dimension serves as a measure of complexity for the group of placed products. The proposed approach for assessing the fill ability of the workspace was validated through experimentation with a group of test models of industrial products, employing a genetic algorithm. The results confirmed the viability of evaluating the effectiveness of product placement in the workspace of an additive machine using fractal analysis. The practical implementation was carried out within the system of technological process planning for additive methods, developed at the Department of “Integrated Technologies of Mechanical Engineering” of NTU “KhPI”.