Additive manufacturing Support structures oriented to trees significantly reduce material consumption

A guest post by Susanne Bader | Translated by AI 4 min Reading Time

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Powder bed-based laser beam melting of metals enables the efficient manufacturing of complex components. A key role is played by the support structures usually required for the construction of 3D components. Promising significant material savings and high scrap safety is a novel support model inspired by bionic algorithms.

Inspired by nature: Bionic support structures for metallic 3D printing bind up to 83 percent less material.(Image: iLAS_TUHH)
Inspired by nature: Bionic support structures for metallic 3D printing bind up to 83 percent less material.
(Image: iLAS_TUHH)

Susanne Bader, technical journalist for technology and industrial topics (automation, IT, Industry 4.0, materials, surface technology) in Munich

When components are produced using selective laser melting (also PBF-LB/M technology), support structures play an important role. They support geometric overhangs and help to avoid inherent stresses and warpage in the component by evenly dissipating heat.

However, these supports also adversely affect the cost of the production process, as their construction ties up material and increases energy consumption. In addition, this leads to extended printing times and increased post-processing effort. This additional time and financial burden poses significant obstacles, particularly for small and medium-sized enterprises. Therefore, it is important to reduce all these points in the interest of economical production.

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Software generates bionic and efficient support structures

In the project "Trees as Efficient Support Structures in Additive Manufacturing" (BEST), Cenit AG and the Institute for Laser and Plant System Technology (iLAS) of the Technical University of Hamburg jointly developed a software tool for the uncomplicated generation of bionic and resource-efficient support structures for additive manufacturing processes. The model was the branched branches of large tree crowns. The project was funded by the Federal Ministry of Education and Research.

Support structures generated from top to bottom

In order to determine the optimal shape and distribution of possible support structures, the cooperation partners compared different types of support structures and evaluated them based on current research. Tree-like structures proved to be the optimal supports in terms of component fixation, thermal properties, and material consumption. To develop a 3D generation tool for creating these support structures, the BEST team first analyzed the well-known botanical algorithms L-Systems and Space Colonization.

  • A deficiency of the L-system was the lack of control in the distribution of the connection points for the branches of the tree structure.

  • However, Space Colonization sometimes produced branches that were too thick, which ultimately caused additional costs.

Therefore, during the development of the software module, a simpler algorithm was used. This generates the supporting tree structures from the crown down to the trunk in the sense of reversed growth.

How tree generation works and its advantages

The BEST tree generation begins with the import of the Step file of the component. The software detects unsupported surfaces and edges. On these, it automatically generates contact points that transition into the trunk via a branch structure as a counter support point. This creates a three-dimensional support structure in the form of a tree, which is visualized together with the component (Figure 1).

Figure 1: The most important parameters of the BEST tree structures.
(Image:iLAS TUHH)

A major advantage of the developed software is its high user-friendliness. The tree structures can be modified and adapted to individual requirements with just a few parameters, even without in-depth knowledge. The fact that the support structures are saved in the Step format is another plus of the tool. Since Step files are not tessellated, they can be manually edited with any CAD system. In addition, the component model in the Step format can also be used for the NC programming of the post-processing. This is because additively manufactured components often need to be machined afterwards. This particularly applies to functional surfaces such as drill holes, threads, contact surfaces and fits.

BEST on the test bench

In order to test the quality and suitability of the created tree supports, the project team conducted a FEM analysis. All steps of the manufacturing process were the subject of this analysis. The primary goal was to compare the BEST support structure with the widely used block supports and the Netfabb internal tree structures (Figure 2). Focal points of the analysis included maximum deformation, material consumption, and the percentage of failed elements. Finite elements in the simulation are considered failed when the yield point of the material is exceeded by the calculated loads.

Figure 2: A component supported by different support bodies.
(Image:Cenit AG)

In the test run, it turned out that the BEST structures far exceeded their competitors in terms of resource consumption: they bind up to 83 percent less material. The maximum deformations of all types of support structures were on a comparable level. Only the BEST supports showed no failed elements in comparison. However, the result of the widely used block supports with 10 percent failed elements should be validated again.

Advantages of biological principles in the PBF-LB/M process proven

Figure 3: Demonstrator component for aviation with tree-like support bodies.
(Image:Cenit AG)

Overall, the BEST team was able to clearly demonstrate the advantages of biological principles in the PBF-LB/M process. At the end of the project, a large and complex demonstrator component from aviation was used to test the developed module under extreme conditions and to show the full potential of the BEST development.

BEST component in the post-processing of additive manufacturing.
(Image:Hein & Oetting Precision Engineering GmbH)

Based on this, an experimental validation of the simulated deformations was carried out by examining the additively manufactured demonstrator with a 3D scanner. The project team is now working to optimize the software tool and to further implement additional features, such as the integration of results from process simulations.

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