Niveau : M.A.Sc.

Data quality assessment of BIM models for facility management


The thesis discusses the limited implementation of Building Information Modeling (BIM) in the facility operation and maintenance (O&M) phase, despite its potential benefits. The main reasons for this include a lack of expertise among owners and operators to effectively use and update as-built BIM models, as well as a lack of industry standards for ensuring ease of use, interoperability, and maintainability. The research aims to bridge this gap by establishing correspondences between as-built models and O&M requirements, creating a checklist for essential information in BIM models, and developing tools to automate this process. A quality framework combining assurance and control is introduced to ensure the models are suitable for operations. The research also outlines a process flow for quality management during model development and handover. Real construction projects were used to validate the effectiveness of the tools and procedures.

Résultats du projet

This research focused on enhancing the quality of Building Information Modeling (BIM) models for facility operation and maintenance (O&M) through a Quality Management (QM) framework. The framework utilizes BIM documentation and Information Requirements (IR) to establish a clear sequence of tasks for optimal FM-BIM delivery. It includes a checklist of essential and redundant items, tailored for specific BIM authoring software like Revit, along with a detailed process flow incorporating Quality Control (QC) tools.
Case studies of real projects were conducted to evaluate the method’s effectiveness in different project stages and contexts. The results highlight the need for owners to define precise information and quality requirements, perform QC tasks during design and construction, and address challenges in manual quality control after project completion.

Contributions du projet

The research contributes to creating more functional FM-BIM models, aligning with owner needs, and ultimately enhancing building operation quality and cost-efficiency. However, there’s potential for further automation using Artificial Intelligence and Machine Learning, as well as adjustments in contract templates for seamless digital facility information delivery. The framework’s applicability across various project types and stages warrants further exploration, along with considerations for data transfer and control in FM platforms. The emergence of OpenBIM platforms and BIM servers provides opportunities for addressing these challenges.


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L’équipe chargée de ce projet

Ali Motamedi


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