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A Review of In Situ Defect Detection and Monitoring Technologies in Selective Laser Melting.
Peng, Xing; Kong, Lingbao; An, Huijun; Dong, Guangxi.
Afiliação
  • Peng X; Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai, China.
  • Kong L; Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai, China.
  • An H; Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai, China.
  • Dong G; Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai, China.
3D Print Addit Manuf ; 10(3): 438-466, 2023 Jun 01.
Article em En | MEDLINE | ID: mdl-37346185
ABSTRACT
The additive manufacturing (AM) technique has received considerable industrial attention, as it is capable of producing complex functional parts in the aerospace and defense industry. Selective laser melting (SLM) technology is a relatively mature AM process that can manufacture complex structures both directly and efficiently. However, the quality of SLM parts is affected by many factors, resulting in a lack of repeatability and stability of this method. Therefore, several common and advanced in situ monitoring as well as defect detection methods are utilized to improve the quality and stability of SLM processes. This article aims at documenting the various defects that occurred in SLM processes and their influences on the final parts. Various types of in situ monitoring and defect detection methods and their applications are reviewed, and their integrations with the SLM processes are also discussed.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article