Abstract: The study aimed to objectively assess the current status and research progress of digital twin technology in industrial engineering both domestically and internationally. It conducts a literature review based on relevant publications from the Web of Science and China National Knowledge Infrastructure (CNKI) databases from 2017 to 2023, and developes a scientific knowledge map. Findings reveal that research on the application of digital twins in the manufacturing field has increased significantly since 2017, with Chinese publications surpassing English ones in frequency. Analysis of contributing institutions identifies significant output from Beihang University, Xi'an Jiaotong University, Northwestern Polytechnical University, University of Patras, and SKKU, indicating a strong academic focus on this area. Keyword analysis distinguishes domestic interests in smart manufacturing, artificial intelligence, and the metaverse, while international research prioritizes Industry 4.0, digital twin design, and system optimization. Domestically, frontier topics revolve around the development of digital twin models, workshops, and data-driven applications. Internationally, the focus shifts to cyber-physical systems, manufacturing systems, and uncertainty analysis. Overall, digital twin technology has currently reached mature applications in industrial engineering, with domestic research concentrating on specific applications and practical exploration, in contrast to international studies' emphasis on model and process optimization.