Quality check of BIM models using machine learning

Abstract

The complexity of BIM models challenges the engaged parties to deliver an ac curate model suitable for various purposes. This is especially important during the construction stage, where errors in construction drawings entail considerable cost and time burdens. As a possible solution, artificial intelligence and machine learning (ML) techniques can be deployed to assist BIM parties with the time and resourceconsuming task of checking the quality of BIM models. This study aims to use ma chine learning techniques to check the quality of BIM models, especially in precast structural wall openings. A machine learning model was used in a BIM model of a project to detect anomalies in openings of precast structural walls, and it was able to detect all the openings with wrong information, which, consequently, would nega tively impact the final delivery of the walls. Considering the applicability of using such an ML model in other projects, the contribution of this study is to reduce the errors in the construction drawings and consequently secure the projects in terms of time and cost burdens due to these errors.