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

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.

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Publication Details

Journal
West Science Information System and Technology
Published
2025-04-30
DOI
https://doi.org/10.58812/wsist.v3i01.1850
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

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

Loso Judijanto
West Science Information System and Technology
Digital Transformation in Industry
article

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

Loso Judijanto
article en

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.

West Science Information System and TechnologyVol. 3(01)
Openalex Percentile: Top 88%
Digital Transformation in Industry
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Artificial Intelligence in Industry 4.0: A Bibliometric Analysis of Research Trends — Loso Judijanto · West Science Information System and Technology (2025) | TGRS Research Map | TGRS