We are an innovative research lab working to transform the digital future of construction by
...
Defining and managing information requirements is the key to deliver the right BIM, for the right reason, with a reasonable amount of effort. These information requirements stem from the various uses BIM aims to offer in a project and serve as a reference to deliver high-quality deliverables and BIM data. Defining these requirements and providing compliant deliverables in an OpenBIM logic is essential to foster collaboration among all stakeholders.
Despite increasing adoption of BIM models across the industry, the quality of BIM deliverables is often unsatisfactory. To address this issue, it is necessary to thoroughly define information requirements and design means to assess them. Therefore, CCPS developed a BIM quality management framework that includes quality control checklists, quality assurance procedures and workflows, and automated tools to assess the quality of BIM deliverables.
The current practice of checking the compliance of BIM models with building codes and standards is labour intensive and prone to human error. At CCPS we investigate various AI-powered methods (rule-based reasoning, natural language processing, machine learning, etc.) to automate the compliance checking processes, i.e., semantic enrichment of models, information extraction, design evaluation, etc.