| Autor: |
Hao-ran Zhou, Hao Yang, Huai-qian Li, Ying-chun Ma, Sen Yu, Jian shi, Jing-chang Cheng, Peng Gao, Bo Yu, Zhi-quan Miao, Yan-peng Wei |
| Předmět: |
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| Zdroj: |
China Foundry; Mar2024, Vol. 21 Issue 2, p101-115, 15p |
| Abstrakt: |
Additive manufacturing technology is highly regarded due to its advantages, such as high precision and the ability to address complex geometric challenges. However, the development of additive manufacturing process is constrained by issues like unclear fundamental principles, complex experimental cycles, and high costs. Machine learning, as a novel artificial intelligence technology, has the potential to deeply engage in the development of additive manufacturing process, assisting engineers in learning and developing new techniques. This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing, particularly in model design and process development. Firstly, it introduces the background and significance of machine learning-assisted design in additive manufacturing process. It then further delves into the application of machine learning in additive manufacturing, focusing on model design and process guidance. Finally, it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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