Rule Inferring for Engineering Quality Risk Management Based on Ontology in Housing Construction

To address the challenges surrounding information sharing and low efficiency during the engineering quality risk management process, this paper constructs a digital process for engineering quality risk management. Engineering quality risk factors were identified through literature analysis and synthesis, and relevant standards, specifications, and project information were collected to construct an engineering quality risk information ontology. The Semantic Web Rule Language (SWRL) was used to implement rule-based rapid identification of risk factors, enabling stakeholders to query information in real-time and perform dynamic information updates promptly. To validate the effectiveness of ontology-based rule inferring for engineering quality risk management, a case study on a project in Guangzhou demonstrated that the proposed rule-inferring effectively identified risk factors and significantly reduced engineering quality risks. The ontology-based digital workflow optimized the engineering quality management workflow and contributed to more efficient and robust risk management practices. The findings provide a meaningful reference for advancing engineering quality risk management methods.