Applications of artificial intelligence and machine learning in metal additive manufacturing

被引:19
|
作者
Ladani, Leila Jannesari [1 ]
机构
[1] Arizona State Univ, Ira A Fulton Sch Engn, Mech & Aerosp Engn, Tempe, AZ 85281 USA
来源
JOURNAL OF PHYSICS-MATERIALS | 2021年 / 4卷 / 04期
关键词
artificial intelligence; metal additive manufacturing; powder bed process; 3D printing; IN-SITU METROLOGY; DIGITAL TWIN; PHASE-TRANSFORMATIONS; RESIDUAL-STRESS; LASER; DEPOSITION; DESIGN;
D O I
10.1088/2515-7639/ac2791
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Artificial intelligence (AI) and additive manufacturing (AM) are both disruptive new technologies. AI has entered many aspects of our lives, but has not been fully realized in the world of AM. Because of the vast amount of data and the digital nature of the technology, AM offers tremendous opportunities in machine learning (ML) and consequently AI. This paper provides a vantage point view of the applications of ML and AI in AM, and specifically in powder bed AM technology. The types of data, sources of data, potential variabilities in experimental and simulation data, and the applicability of these data in ML algorithms are discussed. Several new ideas are presented where fusing these two transformative technologies can potentially have a profound impact on how AM is applied in different fields. A vision on the potential direction of AM to fully realize AI's advantage is provided.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Additive manufacturing trends: Artificial intelligence & machine learning
    Holm, Elizabeth A.
    Williams, James C.
    Herderick, Edward D.
    Huang, Hanchen
    [J]. Advanced Materials and Processes, 2020, 178 (05): : 32 - 33
  • [2] ADDITIVE MANUFACTURING TRENDS: ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
    Holm, Elizabeth A.
    Williams, James C.
    Herderick, Edward D.
    Huang, Hanchen
    [J]. ADVANCED MATERIALS & PROCESSES, 2020, 178 (05): : 32 - 33
  • [3] Artificial intelligence and machine learning applications in biopharmaceutical manufacturing
    Rathore, Anurag S.
    Nikita, Saxena
    Thakur, Garima
    Mishra, Somesh
    [J]. TRENDS IN BIOTECHNOLOGY, 2023, 41 (04) : 497 - 510
  • [4] 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
  • [5] 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
  • [6] Explainable Artificial Intelligence (XAI) and Machine Learning Technique for Prediction of Properties in Additive Manufacturing
    Abbili, Kiran Kumar
    [J]. JOURNAL OF ADVANCED MANUFACTURING SYSTEMS, 2024,
  • [7] Artificial intelligence applications and machine learning
    Agrawal, Prateek
    [J]. Recent Advances in Computer Science and Communications, 2020, 13 (06): : 1113 - 1114
  • [8] A REVIEW OF MACHINE LEARNING APPLICATIONS IN ADDITIVE MANUFACTURING
    Razvi, Sayyeda Saadia
    Feng, Shaw
    Narayanan, Anantha
    Lee, Yung-Tsun Tina
    Witherell, Paul
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2019, VOL 1, 2020,
  • [9] Applications of artificial intelligence and machine learning in orthodontics
    Asiri, Saeed N.
    Tadlock, Larry P.
    Schneiderman, Emet
    Buschang, Peter H.
    [J]. APOS TRENDS IN ORTHODONTICS, 2020, 10 (01) : 17 - 24
  • [10] Applications of machine learning and artificial intelligence in NMR
    Kuhn, Stefan
    [J]. MAGNETIC RESONANCE IN CHEMISTRY, 2022, 60 (11) : 1019 - 1020