An Ontology for Relating Features of Building Product Models with Construction Activities to Support Cost Estimating

It is the cost estimator’s task to determine how the building design influences construction costs. Estimators must account for how and when features of building product models affect the project’s activities, resources, and resource productivity rates that form the basis of a cost estimate. Without explicitly representing estimators’ rationale for relating product and cost information in the computer, estimators must manually detect when and how particular features in a product model affect construction costs, which is a time consuming and error-prone process. Previous research efforts represent the relationships between product, activity, resource, and cost information, and they formalize construction knowledge about how the building design influences construction resources and their productivity. However, they do not provide a common vocabulary and a formal way for estimators to represent their rationale for relating product and cost information to enable automated support of the cost estimating process. This paper presents the ontology we formalized to represent estimators’ rationale for relating product and cost information. The ontology represents the features of building product models that are important to estimators and the estimators’ rationale about how the features affect the activities, resources, and resource productivity rates to calculate construction costs. A software prototype that uses the ontology helps estimators to represent their knowledge formally, and to generate and maintain cost estimates quickly and consistently for feature-based product models. Validation studies of use of the prototype system provide evidence for the power and generality of the ontology. 1 Assistant Professor, Department of Civil Engineering, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4, [email protected] 2 Associate Professor, Department of Civil and Environmental Engineering and (by Courtesy) Computer Science, Director, Center for Integrated Facility Engineering, Stanford University, Stanford, CA 94305, [email protected] 3 Executive Director, Center for Integrated Facility Engineering, Stanford University, Stanford, CA 94305, [email protected] 4 Professor, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, [email protected] 5 Associate Professor, Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, [email protected]