Advancements in machine learning for material design and process optimization in the field of additive manufacturing  

作　　者：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 

机构地区：[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

出　　处：《China Foundry》2024年第2期101-115,共15页中国铸造（英文版）

基　　金：financially supported by the Technology Development Fund of China Academy of Machinery Science and Technology(No.170221ZY01)。

摘　　要：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.

关 键 词：additive manufacturing machine learning material design process optimization intersection of disciplines embedded machine learning 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]