Research Advancements in Digital Twin Technology for Smart Manufacturing - Judijanto, Loso; Vandika, Arnes Yuli (The Eastasouth Journal of Information System and Computer Science, 2025)
This study presents a comprehensive bibliometric analysis of research developments in Digital Twin (DT) technology within the domain of smart manufacturing. Drawing on Scopus-indexed publications from 2010 to 2024, the study explores the growth patterns, thematic structures, institutional contributions, collaborative networks, and emerging research trends using VOSviewer. The findings reveal a sharp increase in publication volume, particularly in 2024, indicating growing academic and industrial interest. China dominates the research landscape in terms of both institutional productivity and international collaboration, followed by India and the United States. Keyword co-occurrence analysis identifies “smart manufacturing,” “digital twin,” and “industry 4.0” as core themes, with increasing emphasis on artificial intelligence, optimization, collaborative robots, and Industry 5.0 in recent years. Co-authorship and country collaboration maps illustrate dense scholarly networks centered around prominent authors and regions. Despite significant progress, the study identifies gaps in real-world implementation, standardization, and ethical considerations. These insights offer valuable direction for future interdisciplinary research and policy strategies aimed at integrating DT technologies into next-generation manufacturing ecosystems.