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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Xian Jing & Rongxin Zhu & Jieqiong Lin & Baojun Yu & Mingming Lu, 2022. "Education Sustainability for Intelligent Manufacturing in the Context of the New Generation of Artificial Intelligence," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14148-:d:957658
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    References listed on IDEAS

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    1. Adesuwa Vanessa Agbedahin, 2019. "Sustainable development, Education for Sustainable Development, and the 2030 Agenda for Sustainable Development: Emergence, efficacy, eminence, and future," Sustainable Development, John Wiley & Sons, Ltd., vol. 27(4), pages 669-680, July.
    2. Francisco M. Moreno-Pino & Rocío Jiménez-Fontana & José María Cardeñoso Domingo & Pilar Azcárate Goded, 2021. "Study of the Presence of Sustainability Competencies in Teacher Training in Mathematics Education," Sustainability, MDPI, vol. 13(10), pages 1-19, May.
    3. Wang, Jian & Wu, Huiqin & Chen, Yan, 2020. "Made in China 2025 and manufacturing strategy decisions with reverse QFD," International Journal of Production Economics, Elsevier, vol. 224(C).
    4. Andrew Bieler & Marcia McKenzie, 2017. "Strategic Planning for Sustainability in Canadian Higher Education," Sustainability, MDPI, vol. 9(2), pages 1-22, January.
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    1. Yavuz Topkaya & Yunus Doğan & Veli Batdı & Sami Aydın, 2025. "Artificial Intelligence Applications in Primary Education: A Quantitatively Complemented Mixed-Meta-Method Study," Sustainability, MDPI, vol. 17(7), pages 1-29, March.
    2. Jun Liu & Meng Sun & Zile Liu & Yanhua Xu, 2023. "Pre-Service Teachers’ Instructional Innovation Capabilities: A Many-Faceted Rasch Model Analysis," SAGE Open, , vol. 13(4), pages 21582440231, December.

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