URGENT UPDATE: A pioneering study has just revealed critical insights into the use of digital twin technology for enhancing facility management, addressing long-standing inefficiencies in the architecture, engineering, construction, and facility management (AEC-FM) industries. Researchers from Western Michigan University, including Obaidullah Hakimi, Hexu Liu, and Osama Abudayyeh, conducted a comprehensive bibliometric review of 248 research articles spanning from January 2012 to March 2022, uncovering vital trends and gaps in current facility lifecycle management practices.
This study comes at a critical time when the operation and maintenance (O&M) phase of facility management is recognized as the longest and most costly segment, yet often neglected. The findings underscore the urgent need for better asset management strategies, highlighting how digital twins can transform decision-making through real-time data acquisition and analysis.
The research identified four primary focus areas: building information modeling (BIM), AI-driven predictive maintenance, real-time cyber-physical system data integration, and facility lifecycle asset management. Additionally, keyword clustering revealed seven main research clusters, including AI-based predictive maintenance and semantic interoperability, which are crucial for advancing the field.
In a significant revelation, the study indicated that while many publications exist, most influential studies remain theory-focused, with a lack of practical case studies demonstrating real-world applications. This gap presents a pressing opportunity for further exploration, especially in areas such as AI-based real-time asset monitoring and autonomous control feedback.
Moreover, the University of Cambridge has emerged as a key contributor, leading in citation impact within the UK, while the journal Automation in Construction is noted as a prominent publication source in this field.
The researchers emphasize the importance of advancing AI capabilities and fostering rich data interoperability to improve overall facility management systems. Their findings signal a vital shift in how the industry can leverage digital twin technology to enhance efficiency and decision-making.
For those interested in diving deeper into this groundbreaking work, the full text of the study, titled “Digital Twin-Enabled Smart Facility Management: A Bibliometric Review“, is available for open access at: https://doi.org/10.1007/s42524-023-0254-4.
Stay tuned for further updates as the implications of this research continue to unfold, influencing the future of facility management worldwide.
