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Facet Connectivity-Based Estimation Algorithm for Manufacturability of Supportless Parts Fabricated via LPBF.
Lee, Seung-Yeop; Lee, Jae-Wook; Yang, Min-Seok; Kim, Da-Hye; Jung, Hyun-Gug; Ko, Dae-Cheol; Kim, Kun-Woo.
  • Lee SY; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology (KITECH), Daegu 42994, Republic of Korea.
  • Lee JW; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology (KITECH), Daegu 42994, Republic of Korea.
  • Yang MS; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology (KITECH), Daegu 42994, Republic of Korea.
  • Kim DH; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology (KITECH), Daegu 42994, Republic of Korea.
  • Jung HG; R&D Center, STACO Co., Ltd., Ansan-si 15433, Republic of Korea.
  • Ko DC; Department of Nanomechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
  • Kim KW; Smart Manufacturing Technology R&D Group, Korea Institute of Industrial Technology (KITECH), Daegu 42994, Republic of Korea.
Materials (Basel) ; 16(3)2023 Jan 24.
Article en En | MEDLINE | ID: mdl-36770047
ABSTRACT
Recent advances in additive manufacturing have provided more freedom in the design of metal parts; hence, the prototyping of fluid machines featuring extremely complex geometries has been investigated extensively. The fabrication of fluid machines via additive manufacturing requires significant attention to part stability; however, studies that predict regions with a high risk of collapse are few. Therefore, a novel algorithm that can detect collapse regions precisely is proposed herein. The algorithm reflects the support span over the faceted surface via propagation and invalidates overestimated collapse regions based on the overhang angle. A heat exchanger model with an extremely complex internal space is adopted to validate the algorithm. Three samples from the model are extracted and their prototypes are fabricated via laser powder bed fusion. The results yielded by the fabricated samples and algorithm with respect to the sample domain are compared. Regions of visible collapse identified on the surface of the fabricated samples are predicted precisely by the algorithm. Thus, the supporting span reflected by the algorithm provides an extremely precise prediction of collapse.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article