Development of BIM-AR-Based Facility Risk Assessment and Maintenance System
Publication: Journal of Performance of Constructed Facilities
Volume 33, Issue 6
Abstract
Although research has shown the potential for integrating building information modeling (BIM) and facility management systems (FMS) and has indicated the importance of using efficient maintenance strategies to reduce facility maintenance management (FMM) costs, there is a paucity of literature that assesses facility risk and strategic actions based on the prioritization of equipment maintenance at the component level. To bridge this gap, this paper developed a facility risk assessment and maintenance system prototype that will enable facility managers to select the maintenance policy for a single piece of equipment and determine the maintenance priorities of equipment components in the initial stage of operation and maintenance (O&M). The maintenance policy was selected by using the analytic hierarchy process (AHP), and facility risk assessment based on fuzzy multiple-criteria decision-making (MCDM) was performed to determine the maintenance priorities of equipment components. In this way, the failure modes of the equipment components and the risk order can be analyzed to support facility maintenance decision-making. A facility maintenance system that has embedded policy and maintenance decisions was then developed. Disruptive technologies, such as BIM and augmented reality (AR), were applied to guide the maintenance processes. Finally, a case study demonstrated system implementation.
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Acknowledgments
The authors extend their appreciation to Project Nos. 106112016CDJSK03XK06 and 2018CDXYJG0047 supported by the Fundamental Research Funds for the Central Universities (China) for vital support. The authors thank the reviewers for their comments which improved the quality of the paper.
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Published In
Journal of Performance of Constructed Facilities
Volume 33 • Issue 6 • December 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Jul 27, 2018
Accepted: Mar 22, 2019
Published online: Sep 14, 2019
Published in print: Dec 1, 2019
Discussion open until: Feb 14, 2020
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