| Title： | Advancements in machine learning for material design and process optimization in the field of additive manufacturing | |
| Author： | Hao-ran Zhou1 , Hao Yang3 , Huai-qian Li1 , Ying-chun Ma1 , Sen Yu4 , Jian shi1 , Jing-chang Cheng1 , Peng Gao1 , Bo Yu1 , Zhi-quan Miao1 , and *Yan-peng Wei1, 2 | |
| Address： | 1. National Key Laboratory of Advanced Casting Technologies, Shenyang Research Institute of Foundry Co., Ltd. CAM, Shenyang 110022, China; 2. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China; 3. Key Laboratory of Space Physics, Beijing 100076, China; 4. School of Materials Science and Engineering, Nanyang Technological University, 639798, Singapore | |
| Key words： | additive manufacturing; machine learning; material design; process optimization; intersection of disciplines; embedded machine learning | |
| CLC Nmuber： | TP391.9 | |
| Document Code： | A | |
| Article ID： | 1672-6421(2024)02-101-15 | |
| Abstract： |
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.
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