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Trends in intelligent manufacturing research: a keyword co-occurrence network based review

Author

Listed:
  • Chenxi Yuan

    (Northeastern University)

  • Guoyan Li

    (Northeastern University)

  • Sagar Kamarthi

    (Northeastern University)

  • Xiaoning Jin

    (Northeastern University)

  • Mohsen Moghaddam

    (Northeastern University)

Abstract

In recent years, driven by Industry 4.0 wave, academic research has focused on the science, engineering, and enabling technologies for intelligent and cyber manufacturing. Using a network science and data mining-based Keyword Co-occurrence Network (KCN) methodology, this work analyzes the trends in data science topics in the manufacturing literature over the past two decades to inform the researchers, educators, industry leaders of knowledge trends in intelligent manufacturing. It studies the evolution of research topics and methods in data science, Internet of Things (IoT), cloud computing, and cyber manufacturing. The KCN methodology is applied to systematically analyze the keywords collected from 84,041 papers published in top-tier manufacturing journals between 2000 and 2020. It is not practically feasible to review this large body of literature through tradition manual approaches like systematic review and scoping review to discover insights. The results of network modeling and data analysis reveal important knowledge components and structure of the intelligent and cyber manufacturing literature, implicit the research interests switch and provide the insights for industry development. This paper maps the high frequency keywords in the recent literature to nine pillars of Industry 4.0 to help manufacturing community identify research and education directions for emerging technologies in intelligent manufacturing.

Suggested Citation

  • Chenxi Yuan & Guoyan Li & Sagar Kamarthi & Xiaoning Jin & Mohsen Moghaddam, 2022. "Trends in intelligent manufacturing research: a keyword co-occurrence network based review," Journal of Intelligent Manufacturing, Springer, vol. 33(2), pages 425-439, February.
    • Handle: RePEc:spr:joinma:v:33:y:2022:i:2:d:10.1007_s10845-021-01885-x
    DOI: 10.1007/s10845-021-01885-x
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    References listed on IDEAS

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    1. Andrew Kusiak, 2019. "Editorial: Intelligent manufacturing: bridging two centuries," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 1-2, January.
    2. Tin-Chih Toly Chen, 2017. "Cloud intelligence in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1057-1059, June.
    3. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    4. Juan Pablo Usuga Cadavid & Samir Lamouri & Bernard Grabot & Robert Pellerin & Arnaud Fortin, 2020. "Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1531-1558, August.
    5. Ahmad Barari & Marcos Sales Guerra Tsuzuki & Yuval Cohen & Marco Macchi, 2021. "Editorial: intelligent manufacturing systems towards industry 4.0 era," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1793-1796, October.
    6. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
    7. Xifan Yao & Jiajun Zhou & Yingzi Lin & Yun Li & Hongnian Yu & Ying Liu, 2019. "Smart manufacturing based on cyber-physical systems and beyond," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2805-2817, December.
    8. S. Lozano & L. Calzada-Infante & B. Adenso-Díaz & S. García, 2019. "Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 609-629, August.
    9. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    10. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    11. Ercan Oztemel & Samet Gursev, 2020. "Literature review of Industry 4.0 and related technologies," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 127-182, January.
    12. Atanu Sengupta & Sanjoy De, 2020. "Review of Literature," India Studies in Business and Economics, in: Assessing Performance of Banks in India Fifty Years After Nationalization, chapter 0, pages 15-30, Springer.
    13. Eeva Järvenpää & Niko Siltala & Otto Hylli & Minna Lanz, 2019. "The development of an ontology for describing the capabilities of manufacturing resources," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 959-978, February.
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