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Automated Knowledge‐Based Design for Additive Manufacturing: A Case Study with Flow Manifolds
Author(s) -
Biedermann Manuel,
Beutler Patrick,
Meboldt Mirko
Publication year - 2022
Publication title -
chemie ingenieur technik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 36
eISSN - 1522-2640
pISSN - 0009-286X
DOI - 10.1002/cite.202100209
Subject(s) - process (computing) , computer science , engineering design process , work flow , work (physics) , manufacturing engineering , flow (mathematics) , design process , systems engineering , engineering drawing , industrial engineering , engineering , work in process , mechanical engineering , operations management , operating system , geometry , mathematics
Additive manufacturing (AM) enables novel process equipment devices. However, the manual 3D design of complex part geometries is frequently challenging as designers need to fulfill functional requirements and consider the restrictions of AM. One promising approach is to automatically generate the design of parts. This work aims to introduce such an automated design approach to practitioners in the area of process engineering. The work describes the basic steps required to develop an automated, knowledge‐based design tool for AM and demonstrates the approach using a case study on flow manifolds.