Tracing the Path from Industry 4.0 to Industry 5.0 through Topic Modeling Analysis

Authors

  • Cheng Zeng College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou, China
  • Hong Cheng Ding INTI International University, Nilai, Negeri Sembilan, Malaysia
  • Wai Yie Leong INTI International University, Nilai, Negeri Sembilan, Malaysia
  • Ya Fei Li College of Foreign Languages, Minjiang University, Fuzhou, China

DOI:

https://doi.org/10.61453/INTIj.202501

Keywords:

Industry 4.0, Industry 5.0, LDA model, Topic evolution, Research hotspots

Abstract

This study explores the evolution of research from Industry 4.0 to Industry 5.0 using Latent Dirichlet Allocation (LDA) to uncover key research topics and trends. This paper utilizes the Web of Science (WOS) database to collect literature on Industry 4.0 and 5.0 from 2015 to 2024. Through an LDA-based analysis, five key topics were identified, including IoT and automation, adoption frameworks, digital business transformation, smart manufacturing systems, and AI-driven models. The research highlights the growing importance of human-machine collaboration, blockchain security, and sustainable practices in the transition from Industry 4.0 to Industry 5.0. This study contributes to the understanding of evolving industrial research and offers insights into the future direction of industrial innovation.

References

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Leogn, W. Y., Leong, Y. Z., & Leong, W. S. (2023). Human-machine interaction in biomedical manufacturing. In 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE) (pp. 939–944). https://doi.org/10.1109/ECICE59523.2023.10383070

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Zhao, W. X., et al. (2021). Topic modeling for research trend analysis in industry sectors. Journal of Supercomputing.

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Published

2025-01-20

How to Cite

Zeng, C., Cheng Ding, H., Leong, W. Y., & Fei Li, Y. (2025). Tracing the Path from Industry 4.0 to Industry 5.0 through Topic Modeling Analysis. INTI Journal, 2025(1), 1–9. https://doi.org/10.61453/INTIj.202501

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Articles