• Ms. Tamanna Agrawal
• Ms.Chhavi Birla
• Mr. Rajeshwar S Deshmukh
• Mr. Jayant Patil

Digital Twin technology has emerged as a transformative enabler for the modern manufacturing industry, providing a virtual representation of physical assets, processes, and systems. As Industry 4.0 advances, Digital Twins are increasingly integrated into production environments to enhance operational efficiency, optimize performance, and support data-driven decision making. This study presents a systematic review of research on the application of Digital Twin models in manufacturing, focusing on their role in improving productivity, enabling real-time monitoring, and supporting predictive and prescriptive maintenance. Research articles published between 2017 and 2024 were examined, and 225 SCOPUS papers were selected for detailed analysis. The Bibliometric Literature Review (BLR) was conducted on different analyses, such as the number of publications year-wise, organization analysis, citation analysis, author-wise analysis, etc. It was found that the most papers were published in China. Additionally, it is concluded that the year-wise publication rate is exponentially increased. This study provides a consolidated understanding of how Digital Twin technology is evolving within the manufacturing industry and highlights key opportunities for future research and industrial adoption.

digital Twin, Manufacturing industries, Bibliometric Literature review, VOSviewer.

"A Bibliometric Literature review on digital twin for manufacturing industry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.a533-a541, December-2025, Available :http://www.jetir.org/papers/JETIR2512072.pdf

"A Bibliometric Literature review on digital twin for manufacturing industry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppa533-a541, December-2025, Available at : http://www.jetir.org/papers/JETIR2512072.pdf