A feature ontology to support construction cost estimating

  • Authors:

  • Sheryl Staub–french;Martin Fischer;John Kunz;Kos Ishii;Boyd Paulson

  • Affiliations:

  • Department of Civil Engineering, University of British Columbia, 2324 Main Mall, Vancouver, British Columbia V6T 1Z4 Canada;Department of Civil and Environmental Engineering, Stanford University and Center for Integrated Facility Engineering, Stanford University, USA;Center for Integrated Facility Engineering, Stanford University, Stanford, California 94305, USA;Department of Mechanical Engineering, Stanford University, Stanford, California 94305, USA;Department of Civil and Environmental Engineering, Stanford University, Stanford, California 94305, USA

  • Venue:
  • Artificial Intelligence for Engineering Design, Analysis and Manufacturing
  • Year:
  • 2003

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Abstract

Construction cost estimators are confronted with the challenging task of estimating the cost of constructing one of a kind facilities. They must first recognize the design conditions of the facility design that are important (i.e., incur a cost) and then determine how the design conditions affect the cost of construction. Current product models of facility designs explicitly represent components, attributes of components, and relationships between components. These designer-focused product models do not represent many of the cost-driving features of building product models, such as penetrations and component similarity. Previous research efforts identify many of the different features that affect construction costs, but they do not provide a formal and general way for practitioners to represent the features they care about according to their preferences. This paper presents the formal ontology we developed to represent construction knowledge about the cost-driving features of building product models. The ontology formalizes three classes of features, defines the attributes and functions of each feature type, and represents the relationships between the features explicitly. The descriptive semantics of the model allow estimators to represent their varied preferences for naming features, specifying features that result from component intersections and the similarity of components, and grouping features that affect a specific construction domain. A software prototype that implements the ontology enables estimators to transform designer-focused product models into estimator-focused, feature-based product models. Our tests show that estimators are able to generate and maintain cost estimates more accurately, consistently, and expeditiously with feature-based product models than with industry standard product models.