Artificial Intelligence in Additive Manufacturing (AI-in-AM): A Scientometric Analysis

被引:0
作者
Kaur, Ravneet [1 ]
Kaur, Mandeep [2 ]
Singh, Malkeet [3 ]
机构
[1] Thapar Inst Engn & Technol TIET, Dept Comp Sci & Engn, Patiala, Punjab, India
[2] Guru Nanak Dev Univ, Dept Comp Sci, Reg Ctr, Jalandhar, Punjab, India
[3] Swinburne Univ Technol, Sch Engn, Hawthorn, Vic, Australia
关键词
Additive manufacturing; artificial intelligence; scientometric analysis; machine learning; neural networks; optimization; CONVOLUTIONAL NEURAL-NETWORK; CRITERIA DECISION-MAKING; BUILD ORIENTATION; SUPPORT STRUCTURE; COMPUTER VISION; MELT-POOL; DESIGN; OPTIMIZATION; PREDICTION; SELECTION;
D O I
10.1142/S0219622025500488
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Additive manufacturing (AM), also known as 3D printing is being widely used in the manufacturing industry. Moreover, from the past few years, there has been an increase in research toward the applicability of artificial intelligence (AI) technologies in the field of AM. The primary reason for the same includes the need to automate and deal with the complex problems in the domain of AM. This paper presents a first-of-its-kind scientometric analysis of the research being conducted toward the use of AI-in-AM. This study helps in uniquely presenting the visualization of data as well as understanding the trends, prominent journals, institutes, countries and topics of research interest and how they are linked with the studies available nowadays on AI-in-AM. Data corresponding to various research papers in this domain were collected from Scopus. Results obtained from the visual analysis indicate that machine learning, deep learning (neural networks), genetic algorithms, industry 4.0 are the most widely adopted AI techniques in the AM. Further deploying these AI techniques, computer-aided design, fabrication, industrial research, optimization, robotics, modeling, image processing are some of the key areas of research. As per the observed scenarios, future research directions such as the applicability of robotics and neural network techniques to AM domains have been emphasized. Also, 4D printing is the new trend with future holding to 5D printing as well. Overall, this study aims to provide a complete reference to researchers as well as industry practitioners regarding the trends and competences when employing AI-in-AM.
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页数:43
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