Education Sustainability for Intelligent Manufacturing in the Context of the New Generation of Artificial Intelligence

Xian Jing, Rongxin Zhu, Jieqiong Lin (), Baojun Yu and Mingming Lu
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Xian Jing: School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China
Rongxin Zhu: School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China
Jieqiong Lin: School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China
Baojun Yu: School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China
Mingming Lu: School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China

Sustainability, 2022, vol. 14, issue 21, 1-14

Abstract: With the continuous breakthrough and innovation of artificial intelligence technology, the demand for diversified and multi-level compound intelligent manufacturing talents keeps growing. However, the current pace of intelligent manufacturing talent education in colleges and universities is still difficult to keep up with the advances in science and technology in the context of the new generation of artificial intelligence. This work conducted visual research of the literature on artificial intelligence in the field of manufacturing. All the literature was retrieved from the Web of Science Core Collection and divided into three periods (1979–1994, 1995–2007 and 2008–2021) according to the fluctuation of literature volume. Bibliometric and content analysis of the related literature during these periods were conducted to track the hotspots and trend of artificial intelligence in the field of manufacturing. The results showed that the internet of things, deep learning, cyber physical systems and smart manufacturing have been the new research hotspots. Finally, a series of suggestions were given for the sustainable education of intelligent manufacturing talents in the context of the new generation of artificial intelligence. This work may provide references for the construction of sustainable education systems for intelligent manufacturing talents in the context of the new generation of artificial intelligence.

Keywords: artificial intelligence; education sustainability; intelligent manufacturing; data visualization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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