Minimizing support structures is crucial in reducing 3D printing material and time. Partition-based methods are efficient means in realizing this objective. Although some algorithms exist for support-free fabrication of solid models, no algorithm ever considers the problem of support-free fabrication for shell models (i.e., hollowed meshes). In this paper, we present a skeleton-based algorithm for partitioning a 3D surface model into the least number of parts for 3D printing without using any support structure. To achieve support-free fabrication while minimizing the effect of the seams and cracks that are inevitably induced by the partition, which affect the aesthetics and strength of the final assembled surface, we put forward an optimization system with the minimization of the number of partitions and the total length of the cuts, under the constraints of support-free printing angle. Our approach is particularly tailored for shell models, and it can be applicable to solid models as well. We first rigorously show that the optimization problem is NP-hard and then propose a stochastic method to find an optimal solution to the objectives. We propose a polynomial-time algorithm for a special case when the skeleton graph satisfies the requirement that the number of partitioned parts and the degree of each node are bounded by a small constant. We evaluate our partition method on a number of 3D models and validate our method by 3D printing experiments.
Reducing the volume of support structures is a critical means for saving materials and budgets of additive manufacturing, and tree structure is an effective topology for this purpose. Although a few articles in literature and commercial software have been devoted to developing tree-supports, those tree-supports are generated based on geometry optimization or user-defined parameters, which cannot guarantee a minimum volume with robust fabrication guarantee. To address this issue, we propose a set of formulas for stably growing the tree-supports with physical constraints based on 3D printing experiments using fused decomposition modelling (FDM) machines, and a volume minimization mechanism using a hybrid of particle swarm optimization (PSO) method and a greedy algorithm. We show that this combination is effective in reducing the volume of tree-supports and the simulations reveal that the volume curves monotonically descent to a constant within a short time, and our experimental results show that the models with the tree-supports can be manufactured stably.
Purpose The purpose of this paper is to design a lightweight tree-shaped internal support structure for fused deposition modeling (FDM) three-dimensional (3D) printed shell models. Design/methodology/approach A hybrid of an improved particle swarm optimization (PSO) and greedy strategy is proposed to address the topology optimization of the tree-shaped support structures, where the improved PSO is different from traditional PSO by integrating the best component of different particles into the global best particle. In addition, different from FEM-based methods, the growing of tree branches is based on a large set of FDM 3D printing experiments. Findings The proposed improved PSO and its combination with a greedy strategy is effective in reducing the volume of the tree-shaped support structures. Through comparison experiments, it is shown that the results of the proposed method outperform the results of recent works. Research limitations/implications The proposed approach requires the derivation of the function of the yield length of a branch in terms of a set of critical parameters (printing speed, layer thickness, materials, etc.), which is to be used in growing the tree branches. This process requires a large number of printing experiments. To speed up this process, the users can print a dozen of branches on a single build platform. Thereafter, the users can always use the function for the fabrication of the 3D models. Originality/value The proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating the shell models using the FDM technique; although the target is to minimize the volume of internal support structures, it is also applicable to the exterior support structures, and it can be adapted to the design of the tree-shaped support structures for other AM techniques such as SLA and SLM.
PurposeThe purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint. Design/methodology/approachA hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments. FindingsThe hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches. Research limitations/implicationsThe proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail. Originality/valueThe proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.
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