期刊
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
卷 114, 期 9-10, 页码 3177-3184出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00170-021-07037-y
关键词
Additive manufacturing; Selective laser melting (SLM); Soft magnetic composite (SMC); Machine learning (ML); Evolutionary algorithm
资金
- Ministry of Science and Technology (MOST) of Taiwan [MOST109-2218-E-006-034]
The parameter selection process for magnetic materials in SLM is complex due to the need to consider iron loss and permeability properties. This research integrates machine and evolutionary algorithms to accurately predict magnetic characteristics and generate process parameter suggestions based on practical demands.
Selective laser melting (SLM) is one of the widely used metal additive manufacturing techniques. While SLM is able to produce high-quality products, the parameter selection process can be very complicated, especially for magnetic materials in that the iron loss and permeability properties must also be considered, which renders the parameter selecting process more complicated. This research explores the parameter selection process of magnetic material for SLM, which integrates machine and evolutionary algorithms to accurately predict magnetic characteristics, such as iron loss and permeability, and generates suggestions for the process parameters according to practical demands.
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