A review of machine learning in additive manufacturing: design and process

被引:0
|
作者
Chen, Kefan [1 ]
Zhang, Peilei [2 ]
Yan, Hua [2 ]
Chen, Guanglong [1 ]
Sun, Tianzhu [3 ]
Lu, Qinghua [2 ]
Chen, Yu [4 ]
Shi, Haichuan [2 ]
机构
[1] School of Mathematics, Physics & amp,Statistics, Shanghai University of Engineering Science, Shanghai,201620, China
[2] School of Materials Science and Engineering, Shanghai University of Engineering Science, Shanghai,201620, China
[3] Warwick Manufacturing Group (WMG), University of Warwick, Coventry,CV4 7AL, United Kingdom
[4] Amplitude Shanghai Laser Technology Company Ltd., Shanghai,200127, China
关键词
177;
D O I
10.1007/s00170-024-14543-2
中图分类号
学科分类号
摘要
引用
收藏
页码:1051 / 1087
相关论文
共 50 条
  • [31] Machine Learning for Additive Manufacturing of Electronics
    Stoyanov, Stoyan
    Bailey, Chris
    [J]. 2017 40TH INTERNATIONAL SPRING SEMINAR ON ELECTRONICS TECHNOLOGY (ISSE), 2017,
  • [32] A hybrid machine learning approach for additive manufacturing design feature recommendation
    Yao, Xiling
    Moon, Seung Ki
    Bi, Guijun
    [J]. RAPID PROTOTYPING JOURNAL, 2017, 23 (06) : 983 - 997
  • [33] Machine learning-based design for additive manufacturing in biomedical engineering
    Wu, Chi
    Wan, Boyang
    Entezari, Ali
    Fang, Jianguang
    Xu, Yanan
    Li, Qing
    [J]. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, 2024, 266
  • [34] Artificial intelligence and machine learning in the design and additive manufacturing of responsive composites
    Wonbong Choi
    Rigoberto C. Advincula
    H. Felix Wu
    Yijie Jiang
    [J]. MRS Communications, 2023, 13 : 714 - 724
  • [35] Artificial intelligence and machine learning in the design and additive manufacturing of responsive composites
    Choi, Wonbong
    Advincula, Rigoberto C.
    Wu, H. Felix
    Jiang, Yijie
    [J]. MRS COMMUNICATIONS, 2023, 13 (05) : 714 - 724
  • [36] A Systematic Literature Review of Machine Learning Approaches for Optimization in Additive Manufacturing
    Breitenbach, Johannes
    Seidenspinner, Friedrich
    Vural, Furkan
    [J]. 2022 IEEE 46TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2022), 2022, : 1147 - 1152
  • [37] Invited review: Machine learning for materials developments in metals additive manufacturing
    Johnson, N. S.
    Vulimiri, P. S.
    To, A. C.
    Zhang, X.
    Brice, C. A.
    Kappes, B. B.
    Stebner, A. P.
    [J]. ADDITIVE MANUFACTURING, 2020, 36
  • [38] A bibliometric review on application of machine learning in additive manufacturing and practical justification
    Ma, Quoc-Phu
    Nguyen, Hoang-Sy
    Hajnys, Jiri
    Mesicek, Jakub
    Pagac, Marek
    Petru, Jana
    [J]. APPLIED MATERIALS TODAY, 2024, 40
  • [39] Role of Machine Learning in Additive Manufacturing of Titanium Alloys-A Review
    Paturi, Uma Maheshwera Reddy
    Palakurthy, Sai Teja
    Cheruku, Suryapavan
    Darshini, B. Vidhya
    Reddy, N. S.
    [J]. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2023, 30 (08) : 5053 - 5069
  • [40] Raster Angle Prediction of Additive Manufacturing Process Using Machine Learning Algorithm
    Ulkir, Osman
    Bayraklilar, Mehmet Said
    Kuncan, Melih
    [J]. APPLIED SCIENCES-BASEL, 2024, 14 (05):