Ontological inference of work item based on BIM data

Abstract

When engineers prepare a construction cost estimate for budgeting purposes, they use plans, specifications, and available cost data at the completion of the building design phase. They usually take off the quantities of material and related work items and assign appropriate unit costs. In this case, unit cost assignment is solely at the engineer's professional discretion. Building Information Modeling (BIM) is widely adopted in the building construction industry. Tools can be used to automate material quantity, minimizing the time necessary for engineers to engage in the quantity measuring process. This function, however, does not provide any information on work items that are related to materials in the Bill of Quantity (BOQ). Thus, engineers still need to verify associated work items and assign unit costs. This research proposes an ontological inference of work item that enables an automated search of the most appropriate work items and their associated unit costs. This ontology contains semantic information for work items and work conditions, as well as a semantic reasoning rule that activates the ontology. A case study confirms that the proposed ontology and semantic reasoning rule can work in real-world situations. This paper contributes by eliminating subjective decision-making via search of appropriate work items for cost estimation and the use of BIM data extracted from IFCXML. The proposed ontological approach to building cost estimation will assist engineers in more readily using BIM data from IFCXML and will be helpful in automation of the whole estimation process.