Automation of shape quality control for precast concrete members using 3D scanning and BIM: A field-driven smart construction framework

This study presents a BIM-integrated automated shape quality control framework for precast concrete elements, designed to enhance accuracy, efficiency, and traceability in industrial inspection processes. The proposed five-stage workflow combines 3D laser scanning, point-cloud preprocessing, two-stage registration (edge-point alignment and Iterative Closest Point refinement), deviation analysis, and BIM-linked reporting. Using a dataset of 820 precast arch segments, the method achieved a mean registration RMSE of 1.58 mm, representing a 43% improvement in dimensional accuracy compared to manual inspection. The fully automated process reduced inspection time by 40% and achieved 100% defect-detection sensitivity while maintaining consistency under variable environmental conditions. Color-coded deviation heatmaps and digital audit reports were automatically linked to BIM object identifiers, ensuring full compliance with ISO 19650 and ISO 9001 standards for information and quality management. The results demonstrate that the proposed method provides a practical foundation for digital transformation in precast production and aligns with the objectives of Smart Structural Systems by establishing a data-driven, ISO-compliant, and scalable framework for automated geometric quality assurance.