Publications / 2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada

Automatic Classification of Design Conflicts Using Rule-based Reasoning and Machine Learning—An Example of Structural Clashes Against the MEP Model

Ying-Hua Huang and Will Y. Lin
Pages 324-331 (2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada, ISBN 978-952-69524-0-6)

With the emergence of 3D technologies in a recent decade, BIM software makes it easy to detect those conflicts in the early stage of a project. Clash detection in BIM software is now a common task. Among those conflicts found by BIM software, however, a relatively high percentage belongs to ‘pseudo conflicts’—which are permissible or tolerable, but BIM software does not reveal this information. Thus, currently BIM managers have to manually inspect every detected conflict to classify the type of conflict. Some researchers urged an automated process to facilitate this laborious process. This study implemented both a rule-based reasoning system and machine learning classifiers to help classify those BIM-detected conflicts. Preliminary testing results indicate that machine learning algorithms can achieve comparable results to a traditional rule-based system, but with much less costs and energy in developing.

Keywords: Clash detection, Machine learning, Rule-based reasoning, BIM