Detection of design changes is essential for collaboration and version management in the design process of buildings. However, current detection methods based on Building Information Modeling (BIM) usually cause unreliable or meaningless results. This is because most of the current researches look at the question from a data change view, which sometimes is meaningless from a designer’s view. To overcome this problem, this paper first classifies and identifies meaningful design changes from a designer’s view, and develops exemplary BIM models of typical design changes. In this paper, categories of data changes are divided into property data, appearance data and relationship data, and design changes are classified into instance level, type level and model level from a designer’s view. The test of two BIM tools (Autodesk BIM360 and IFCdiff) with developed BIM models shows that the detection results for changes at instance level are perfect while detection results for type and model level still need to be further improved. This work contributes a new view and classification method of design changes, and also sets up a baseline model database for further development and validation of relevant methods and tools.
This work was supported by the National Key R&D Program of China (No. 2018YFD1100900), the Beijing Natural Science Foundation (No. 8194067), the Beijing Municipal Science and Technology Project (No. Z181100005918006), the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (No. QNRC2016001) and the Tsinghua University-Glodon Joint Research Centre for Building Information Model (RCBIM).