Digital Twins for asset management: platform for predictive maintenance and Trough Bridge case study

Digital twins (DT) are seen as a transformative solution for the Engineering & Construction (E&C) industry’s challenges. However, there is a gap between DT research and operational applications. This paper proposes a framework for a DT, exemplified by a trough bridge case study at Luleå University of Technology (LTU). Traditional bridge management relies on manual, time-consuming methods, leading to reduced accuracy and reliability. The DT platform integrates a 3D model with real-time Structural Health Monitoring (SHM) data, providing a collaborative environment for asset management. The proposed platform can be scalable to other structures; it facilitates data interpretation and decision-making, offering a step towards enhanced asset management practices. By bridging the gap between potential and operational applications of DT technology, this study contributes to the evolution of efficient asset management practices in the E&C industry.