Digital Twin and BIM synergy for predictive maintenance in smart building engineering systems development
School of Engineering and Computer Science, Concordia University, Montreal, Canada.
Review Article
World Journal of Advanced Research and Reviews, 2020, 08(02), 406-421
Article DOI: 10.30574/wjarr.2020.8.2.0409
Publication history:
Received on 03 November 2020; revised on 08 November 2020; accepted on 11 November 2020
Abstract:
The rapid evolution of smart building engineering has redefined how modern infrastructure is designed, operated, and maintained. At the intersection of this transformation lies the convergence of Digital Twin technology and Building Information Modelling (BIM), offering a dynamic and data-driven approach to predictive maintenance. Digital Twins, which serve as real-time virtual replicas of physical assets, when integrated with the information-rich environment of BIM, enable enhanced visibility, control, and foresight into building system performance. This synergy bridges the gap between design and operation, fostering a proactive maintenance culture within increasingly complex built environments. This paper investigates how the integration of BIM and Digital Twin frameworks supports predictive maintenance strategies in smart building systems. It explores the foundational principles of each technology and examines their interoperability in creating self-aware, responsive infrastructures. Emphasis is placed on real-time sensor integration, historical data mapping, anomaly detection, and the simulation of future scenarios to anticipate system failures before they occur. Through the implementation of Digital Twin-BIM ecosystems, facility managers and engineers gain continuous insights into HVAC, lighting, structural, and safety systems, thereby reducing downtime, optimizing performance, and extending asset life cycles. The study also outlines the challenges in deploying this hybrid model, including data standardization, interoperability gaps, and the need for cross-domain collaboration. Case references illustrate how early adopters have leveraged this synergy for smart facilities management and sustainable building lifecycle planning. Ultimately, the convergence of Digital Twins and BIM represents a paradigm shift toward intelligent, self-maintaining infrastructure, signaling a new era of digitally augmented engineering practices.
Keywords:
Digital Twin; Building Information Modelling (BIM); Predictive Maintenance; Smart Buildings; Lifecycle Management; Sensor Integration
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Copyright © 2020 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0