Artificial Intelligence in Industry 4.0: A Bibliometric Analysis of Research Trends

Authors

  • Loso Judijanto IPOSS Jakarta, Indonesia

DOI:

https://doi.org/10.58812/wsist.v3i01.1850

Keywords:

Artificial Intelligence, Industry 4.0, Bibliometric Analysis, Machine Learning, Manufacturing

Abstract

The integration of Artificial Intelligence (AI) into Industry 4.0 has revolutionized industrial processes through the implementation of intelligent automation, predictive analytics, and interconnected systems. This study conducts a comprehensive bibliometric analysis to map the research trends, thematic evolution, influential authors, and international collaboration networks within the domain of AI and Industry 4.0. Data were retrieved from the Scopus database, focusing on peer-reviewed journal articles published between 2013 and 2024. Using VOSviewer for data visualization, the analysis reveals five major thematic clusters, with “Industry 4.0,” “machine learning,” “Internet of Things,” and “smart manufacturing” as dominant keywords. The temporal mapping indicates a shift from core technical research toward more strategic themes such as sustainability, digital transformation, and Industry 5.0. Author collaboration networks show regional clusters with limited interdisciplinary integration, while country-level analysis highlights India, Germany, China, and Italy as major contributors. The findings emphasize the field's dynamic growth and underscore the need for more inclusive, cross-disciplinary, and globally connected research agendas to fully realize the potential of AI in the context of Industry 4.0.

References

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Published

2025-04-30

Issue

Vol. 3 No. 01 (2025): West Science Information System and Technology

Section

Articles

License

Copyright (c) 2025 Loso Judijanto

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to Cite

Artificial Intelligence in Industry 4.0: A Bibliometric Analysis of Research Trends (L. Judijanto , Trans.). (2025). West Science Information System and Technology, 3(01), 75-83. https://doi.org/10.58812/wsist.v3i01.1850