Browse by author
Lookup NU author(s): Dr Xiang XieORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
Author(s): Lu QC, Xie X, Heaton J, Parlikad A, Schooling J
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing SOHOMA 2019
Year of Conference: 2019
Print publication date: 03/08/2019
Online publication date: 03/08/2019
Acceptance date: 31/05/2019
Library holdings: Search Newcastle University Library for this item
Series Title: Studies in Computational Intelligence