The Application of BIM-Enabled Facility Management System in Complex Building

The Application of BIM-Enabled Facility Management System in Complex Building

Jun Wang, Shirong Li, Xiangyu Wang, Chao Mao, Jun Guo
Copyright: © 2013 |Pages: 18
DOI: 10.4018/ij3dim.2013070102
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Abstract

Facility Management (FM) is well known for its interdisciplinary knowledge and along with the growing number of green buildings and low-carbon buildings, the FM system become increasingly complex. Many practitioners consider Building Information Modeling (BIM) as the most important technology to bring about improvements. The purpose of this paper is to develop a BIM-enabled FM system which integrates FM, BIM and building management system to improve information sharing and monitoring, FM system control, and equipment management. A case study is implemented to validate the feasibility of the BIM-enabled FM system. Four functionalities are demonstrated in detail: Equipment Information Monitoring (EIM), Dynamic Data Display and Warning (D3W), Energy-Saving Analysis (ESA), and Intelligent Fire Escape Route (IFER). The results show that BIM-enabled FM system facilitates the FM more accurate, timely, safe and efficient.
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This section presents an up-to-date review of FM and BIM research in building industry.

Facility Management

Past studies about FM are mainly concentrated on the following aspects: Innovation process for FM (Mudrak et al., 2005; Sharma et al., 2007; Lavy 2008; Madritsch and7 May 2009), measurement system for FM (De Toni et al., 2007; Meng and Minogue 2011), End-user requirements for green FM (Nousiainen and7 Junnila 2008), and improvement for FM (Lennerts et al., 2005; Leung et al., 2005; Pennanen et al., 2005; Lavy 2008). Some IT technologies has been applied to improve FM. Bae et al. (2013) presented a new vision-based mobile augmented reality system that allowed field personnel to query and access 3D cyber-information on-site by using photographs taken from standard mobile devices. The user’s location and orientation were purely derived by comparing images from the user’s mobile device to a 3D point cloud model generated from a set of pre-collected site photographs. Mhalas et al. (2013) presented a methodology that integrated these energy databases with visualization systems and multi-criteria decision analyses to enable the evaluation of the environmental and financial implications of various energy efficiency and renewable energy interventions at both building and neighborhood levels. In order to improve maintenance crews’ productivity, Augmented Reality (AR) is engaged in FM, such as facilitating piping assembly (Hou and7 Wang 2011; Hou et al., 2013; Hou et al., 2013), assistant view for 2D drawings (Wang and7 Dunston 2006; Wang and7 Dunston 2013), work process visualization (Henderson and7 Feiner, 2011; Lee and7 Akin, 2011; Dong and7 Kamat, 2013; Golparvar-Fard and7 Ham, 2013), and maintenance information accessing (Irizarry et al., 2013). As-built building information, including building geometry and features, is useful in FM. However, the current process for capturing, retrieving, and modeling such information is labor-intensive and time-consuming. Zhu and Donia (2013) had investigated the potentials of fusing visual and spatial data for automatically capturing, retrieving, and modeling as-built building geometry and features.

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