Paper Title
Process of BIM and Ontology-Based Automation For Estimation of Building Repair and Replacement Costs

It is important to consider initial construction costs and also maintenance cost, operation cost, and end-of-life costs, which together are called the life cycle cost (LCC). LCC analysis is compulsory in Korea per various regulations and systems. Increasingly, the construction industry must deal with a large amount of information and building information modeling (BIM) is now being implemented to address this issue. Therefore, it is inevitable that the use of BIM in construction and LCC analysis in the pre-construction phase will inevitably need to be brought together. This research proposes an ontological approach to automatic BIM-based estimation of repair and replacement costs. This will overcome current problems in cost estimation of repair and replacement. Such estimates are currently done thru a manual process that lends toward inefficiency and subjectivity. The proposed methodology of the study is as follows. First, analyze repair and replacement criteria currently applied overseas and in Korea. Second, define the route of extraction IFC (Industry Foundation Classes) data from the BIM model that describes each of the required elements for estimating repair and replacement costs. Finally, suggest a process of automation to estimate repair and replacement costs thru an Initial Construction Cost Estimation Ontology (ICCEO) that recommends the most adequate work item in order to map with cost information and the Repair and Replacement Cost Estimation Ontology (RRCEO) that refers to initial construction costs as recommended by ICCEO. Using the proposed process is more objective and accurate for obtaining estimated R&R costs. The use of IFC is more accurate and it is more consistent to infer appropriate R&R criteria and information based on ontology technology. Index Terms- BIM, LCC, Repair and Replacement(R&R) cost estimation, Semantic Web, Ontology, Automation system