From BIM towards digital twin: Strategy and future development for smart asset management

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Abstract

With the rising adoption of Building Information Model (BIM) for asset management within architecture, engineering, construction and owner-operated (AECO) sector, BIM-enabled asset management has been increasingly attracting more attentions in both research and practice. This study provides a comprehensive review and analysis of the state-of-the-art latest research and industry standards development that impact upon BIM and asset management within the operations and maintenance (O&M) phase. However, BIM is not always enough in whole-life cycle asset management, especially in the O&M phase. Therefore, a framework for future development of smart asset management is proposed, integrating the concept of Digital Twin (DT). DT integrates artificial intelligence, machine learning and data analytics to create dynamic digital models that are able to learn and update the status of the physical counterpart from multiple sources. The findings will contribute to inspiring novel research ideas and promote widespread adoption of smart DT-enabled asset management within the O&M phase.

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APA

Lu, Q., Xie, X., Heaton, J., Parlikad, A. K., & Schooling, J. (2020). From BIM towards digital twin: Strategy and future development for smart asset management. In Studies in Computational Intelligence (Vol. 853, pp. 392–404). Springer Verlag. https://doi.org/10.1007/978-3-030-27477-1_30

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