Publications / 2014 Proceedings of the 31st ISARC, Sydney, Australia

A Knowledge-Based Framework for Quantity Takeoff and Cost Estimation in the AEC Industry Using BIM

S. Aram, C. Eastman, R. Sacks
Pages 434-442 (2014 Proceedings of the 31st ISARC, Sydney, Australia, ISBN 978-0-646-59711-9, ISSN 2413-5844)

An important set of information provided through Building Information Modeling (BIM) platforms are quantitative properties of design elements and assemblies. The capability to extract or deduce such quantitative properties from explicit and implicit model information is essential for bidding, procurement, production planning, and cost control activities in the AEC projects. Current solutions for quantity take off (QTO) and cost estimation (CE) are developed based on the assumptions that the design models are suitable, contain adequate information to perform these tasks efficiently and accurately. In practice often these criteria do not exist in the models that cost estimators receive. Many estimators, engineers and managers distrust BIM operations as a result or find it difficult to adopt a BIM-based preconstruction process. This leads to a cumbersome, manual and error-prone QT and CE process currently used by most construction companies. In order to overcome these shortcomings, we have developed a framework for a knowledge-based system to perform model based QTO and CE. This framework includes domain, reasoning, task and interface layers. This paper reports on the progress on an ongoing research effort which so far mostly focused on developing a domain layer and rule libraries for the reasoning layer. The domain layer contains a knowledge base which along with rule libraries were developed by acquiring and representing domain expertsÂ’ knowledge. The rule libraries include modules of rules to infer knowledge about different product features. The inferred knowledge will enable providing and representing model information in a compatible format for QTO and CE tasks. It facilitates filtering, grouping and representing feature information provided in design models based on criteria that determines their true cost behavior. Finally, this knowledge will enable forecasting the properties of product features absent from design models. Examples are drawn from various fields inside and outside of the AEC industry, with a focus on the precast concrete industry.

Keywords: Knowledge based systems, knowledge inference, quantity take off, cost estimation, precast concrete