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Lookup NU author(s): Professor Mohamad Kassem
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2016 The author(s). Accurate and valid data is essential during the development of building projects and throughout the use phase of buildings. This study proposes a framework to help owners and facility managers in: (a) defining the requirements for asset management tasks in a structured way; (b) validating project and asset data against the established requirements; and (c) visualising asset data, stored in different and distributed sources, in an integrated and interactive way to support specific asset/facility management functions (e.g. maintenance tasks). The framework combines the use of Information Delivery Manual (IDM), Industry Foundation Classes (IFC), Construction Operations Building Information Exchange (COBie), and Content Management Interoperability Services (CMIS) in the development of Asset Information Models (AM) to fulfil the owner's requirements (Asset Information Requirements) throughout the lifecycle of a building. An AIM is a data model that contains all digital data (graphical, non-graphical, and documentary) required to operate an asset or portfolio of assets. Validation methods are identified for each of the AIM data types and a method for their integration and visualisation is proposed and implemented in a virtual environment. The proposed framework was tested in two use cases that involved (1) the validation of the various data sources against the client requirements, defined in the Asset Information Requirement (AIR); and (2) the visualisation of asset data required for a maintenance task in an interactive virtual environment. The two use cases demonstrated the capability of the framework to enable the definition of AIR and the validation of the different AIM's data deliverables. The visualisation of the AIM data - from different and distributed sources - for a maintenance task was successfully performed in an integrated and interactive game environment. Future work will consider other data sources and will evaluate the proposed framework using real industrial data.
Author(s): Patacas J, Dawood N, Greenwood D, Kassem M
Publication type: Article
Publication status: Published
Journal: Journal of Information Technology in Construction
Online publication date: 30/11/2016
Acceptance date: 31/10/2016
Date deposited: 07/07/2022
ISSN (print): 1874-4753
ISSN (electronic): 1400-6529
Publisher: Department of Computer Science