An Algorithm for Powder Cleaning of Additively Manufactured Parts with Interior Channels

Date

2022-10-06

Author

Öztaşkın, Alptuğ
Yaman, Ulaş

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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With the increasing adoption of Additive Manufacturing (AM) technologies, direct manufacturing of parts with complex interior geometries has become possible. However, for most of the Powder Bed (PB) approaches, powder removal is the bottleneck for manufacturability, it constitutes a design limit. Even on technologies like Selective Laser Melting (SLM), where the powder is not strictly adhered to the surface and gravity would be enough to clean the inner powder, complex channel structures made the cleaning by manual rotation virtually impossible. In this study, an algorithm is proposed to detect inner channels and exit points of a mesh file (of STL or OBJ format) and to form a graph of the inner channel structure. Furthermore, for each node on the graph, the shortest path to exit points is found, which allows the formation of a tree-type data structure. The algorithm is realized using Python programming language and the related libraries. Series of rotational motions (lists of angles and durations) that would allow total powder removal are obtained. Even though the skeleton generation and exit point detection take time, the algorithm is promising with some performance enhancements.

URI

https://hdl.handle.net/11511/106493

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Department of Mechanical Engineering, Conference / Seminar