The Development of an Automated System for a Quality Evaluation of Engineering BIM Models: A Case Study

Author:

Valinejadshoubi Mojtaba12,Moselhi Osama2,Iordanova Ivanka3ORCID,Valdivieso Fernando1,Shakibabarough Azin12,Bagchi Ashutosh2ORCID

Affiliation:

1. Innovation Team, Pomerleau Inc., 500 Rue Saint-Jacques, Suite 300, Montreal, QC H2Y 0A2, Canada

2. Department of Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd. West., Montreal, QC H3G 1M8, Canada

3. Department of Construction Engineering, École de Technologie Supérieure (ÉTS), 1100 Notre-Dame St W, Montreal, QC H3C 1K3, Canada

Abstract

The growing adoption of Building Information Modeling (BIM) within the architectural, engineering, and construction (AEC) sector raises questions about the quality of BIM data deliverables for project owners. Therefore, assessment and evaluation of such BIM data against relevant documents such as the BIM Execution Plan (BEP), the Level of Definition (LOD)/Level of Information (LOI) matrix, and quality control customized checklists become critical, especially in large construction projects. This study primarily aims to create an automated system for assessing the quality of 3D BIM model data, utilizing a proposed project quality control checklist. The automated system consists of four key elements: a BIM-based model, a Data Extraction and Analysis Module, a Data Storage Module, and a Data Visualization Module. The Data Extraction and Analysis Module extracts relevant information and parameters from BIM models to evaluate their quality against predefined checklists. Then, it transfers the information and stores the results in a database. The database is connected to an engineering project collaboration tool, ProjectWise, to automatically update and store the data in the cloud. The database is then connected to an interactive data visualization platform, Power BI, to enable automatic visualization of the generated quality assessment results of the BIM models’ data. This system was applied to a Canadian infrastructure construction project by its BIM department during the preliminary and detailed design phases. It demonstrated an average quality score (AQS) of 87.6% for the BIM models and significantly reduced failing items by around 30%. This study concludes that the system offers a robust, practical solution for enhancing the quality control process in BIM model data management, thereby aiding engineers in timely model adjustments to meet project requirements.

Publisher

MDPI AG

Reference43 articles.

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