Project completed in 2020
Level: M.A.Sc.

Data quality assessment of BIM models for facility management

Abstract

The thesis discusses the limited implementation of Building Information Modeling (BIM) in the operation and maintenance phase of facilities, despite its potential benefits. The main reasons are the lack of expertise on the part of owners and operators to effectively use and update as-built BIM models, and the absence of industry standards to guarantee ease of use, interoperability and maintainability. The research aims to fill this gap by mapping as-built models to operation and maintenance requirements, creating a checklist of essential information in BIM models and developing tools to automate this process. A quality framework combining assurance and control is introduced to ensure that models are fit for purpose. The research also describes a quality management process during model development and delivery. Real construction projects were used to validate the effectiveness of the tools and procedures.

Project results

This research focused on improving the quality of building information modeling (BIM) models for facility operation and maintenance through a quality management (QM) framework. This framework uses 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 elements, adapted to specific BIM creation software such as Revit, as well as a detailed process flow incorporating quality control (QC) tools.
Case studies of real projects were carried out to assess the effectiveness of the method at different stages and in different contexts. The results underline the need for project owners to define precise information and quality requirements, carry out quality control tasks during design and construction, and meet the challenges of manual quality control after project completion.

Project contributions

Research helps create more functional FM-BIM models, align with owners’ needs and, ultimately, improve the quality of building operations and profitability. However, there is potential for further automation through artificial intelligence and machine learning, as well as adjustments in contract models for seamless delivery of digital plant information. The applicability of the framework to different project types and stages deserves further exploration, as do considerations relating to data transfer and control in FM platforms. The emergence of OpenBIM platforms and BIM servers offers opportunities to meet these challenges.

Publications

Publications from this project are available below:

Motamedi, A., Leygonie, R., Forgues, D., & Vaudou, S. (2019) Process Re-Engineering in Owner Organizations to Improve BIM-Based Project Delivery Using Requirements Management Platform. 4th International Conference on Civil and Building Engineering Informatics (ICCBEI). https://www.researchgate.net/publication/339630638_Process_Re-Engineering_in_Owner_Organizations_to_Improve_BIM-Based_Project_Delivery_Using_Requirements_Management_Platform

Leygonie, R., Motamedi, A., & Iordanova, I. (2022) Development of quality improvement procedures and tools for facility management BIM. Developments in the Built Environment. https://doi.org/10.1016/j.dibe.2022.100075

Research team

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Team

The project team

Thesis

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