Reducing construction quality costs through ontology-based inspection planning

Building construction constitutes a specialized and project-specific procedure, encompassing numerous risks. In particular, risks related to execution and the associated costs of defects are a constant challenge for the architectural engineering and construction (AEC) industry. To achieve a balance between the optimum level of quality and the associated costs, knowledge of the composition of quality-related costs is required. In this paper, the objective is to automatically determine expected appraisal costs (ACs) and nonconformity costs (NCCs) from building information modeling (BIM) objects by using semantic web technologies. The ontology for construction quality assurance (OCQA), which is used for the automated planning of quality inspections serves as the initial ontology in this paper. Based on model data, historical quality data, and potential NCCs, the expected quality defects are determined and evaluated using shapes constraint language (SHACL) rules, with the ACs for the corresponding preventive inspections calculated simultaneously. The functionality of the ontology and its rules is demonstrated by defect type unevenness of screed. • Ontology-based model for appraisal and nonconformity costs in construction • Detection of potential defects from historical data • Support for decision making in inspection planning