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- W2155816150 abstract "Managing changes is critical for a successful energy efficient retrofit project. Good change management (CM) enables the evaluation of change dependencies and effects, and it is essential to controlling and mitigating failure factors in projects. For example, inappropriate management may generate disruptive impacts on energy efficiency goals. The use of Building Information Modeling (BIM) has facilitated the delivery of both new build and retrofit projects but there is inadequate support for the management of changes, and very little research has been conducted to integrate CM processes within BIM. This paper aims to specify an integrated framework for embedding CM in BIM. The framework has been developed within the BIM Data Hub project, which focuses on developing a central repository of building information, to manage potential changes to IFC-based models. Current work on the BIM Data Hub focuses on retrieving domain-specific information from IFC models to conduct energy analysis. The outcomes of the analysis may result in recommendations for better energy performance, which would trigger potential changes. Such changes should be adequately managed across the building lifecycle. A comprehensive review of literature was conducted, including the developments and current status of CM and BIM adoption in energy efficient retrofits. The requirements and challenges for the integration of CM and BIM Data Hub were also investigated. Subsequently, the paper formulated a mechanism for how changes resulting from workflow execution can be updated on BIM models, and how change information can be disseminated among team members. A system platform was developed based on the integrated framework. Finally, the contributions and recommendations for future research are presented." @default.
- W2155816150 created "2016-06-24" @default.
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- W2155816150 date "2014-06-17" @default.
- W2155816150 modified "2023-10-18" @default.
- W2155816150 title "A Framework for Integrating Change Management with Building Information Modeling" @default.
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- W2155816150 doi "https://doi.org/10.1061/9780784413616.055" @default.
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