Evaluating the Use of Blockchain-Enabled Federated Learning for Smart Manufacturing: A Bibliometric Review

The combination of blockchain technology, federated learning, and smart manufacturing has gained significant interest due to its potential for data sharing, security, and collaborative learning in industrial environments. This article presents a bibliometric review that provides a thorough examination of the use of blockchain-enabled federated learning in the context of the Industrial Internet of Things and smart manufacturing. We performed a literature search across multiple academic databases, including Scopus and Web of Science (WoS). We performed a comprehensive literature search across Web of Science, and Scopus, using tailored search strings. After data preprocessing and deduplication, a final set of 225 peer-reviewed journal articles was included for analysis. For the visualization, we have used VoSViewer and Python data science libraries. Bibliometric techniques, including publication trend analysis, author productivity analysis, journal impact assessment, and network visualizations, were employed to quantify and explore the research areas. The results revealed an upward trend in publications, with a surge in recent years, indicating growing interest in this domain. Influential authors, institutions, and countries contributing to the field were identified, shedding light on potential research collaborations and knowledge hubs. Additionally, we performed a content analysis to highlight emerging research themes, challenges, and future directions. To the best of our knowledge, this is the first bibliometric study that evaluates the use of blockchain-enabled federated learning for smart manufacturing.