Bibliometric analysis of industry 4.0 applications literature: Analysis of trends, citations and publication models

In this study, a bibliometric analysis was conducted to examine the academic literature on Industry 4.0 applications in detail. Developments such as digitalisation, artificial intelligence, the Internet of Things, big data, and automation are increasingly affecting production systems, which leads to a rapid diversification of academic studies. In this context, the study comprehensively examined the scientific impact, citation dynamics, publication patterns, and collaboration networks of publications related to production processes based on data obtained from the Web of Science database by using various keywords for narrowing down the scope. Visualisation tools such as VOSviewer, Gephi, and Tableau were used in the bibliometric analysis to detail keyword trends, regional leadership, and inter-institutional interactions. The findings reveal how trends in the literature have evolved over time and offer important recommendations for future studies. The relevant literature emphasises that production processes, when combined with Industry 4.0, provide businesses with a competitive advantage and improvements in efficiency, capacity, quality, innovation, and customer satisfaction. According to the research findings, scientific output has increased significantly, with an annual increase of approximately 40% since 2018. Co-authorship networks have also grown, highlighting increasing global collaboration between institutions in China, the United States and Western Europe. Thematic analysis indicates that early studies focused on areas such as cyber-physical systems and automation, while recent academic studies have shifted towards more specialised topics such as artificial intelligence (AI), the Internet of Things (IoT), digital twins and explainable AI. The research provides academic researchers with guiding information on the current state of Industry 4.0 literature and potential areas for development. In this regard, the study is expected to provide valuable contributions to new academic research in the fields of production technologies and digital transformation.