A Closed-Loop Digital QA/QC Framework for Mega Construction Projects: Integrating BIM, Reality Capture, AI and Enterprise Systems

Quality management in mega construction projects is increasingly supported by digital technologies, yet quality information often remains fragmented across inspection systems, reality-capture platforms, Building Information Modelling (BIM) environments and enterprise systems. This fragmentation limits traceability, delays corrective actions and weakens the connection between quality performance, contractual obligations and financial accountability. This study develops a closed-loop digital QA/QC framework that integrates BIM, mobile field inspection, reality capture, artificial intelligence (AI) augmentation and enterprise resource planning (ERP) within a unified governance architecture. Following a Design Science Research approach, the study proposes a seven-layer framework linking quality events to procurement, financial control, and project-management processes while supporting role-based decision-making through data democratisation mechanisms. The framework extends conventional ERP-enabled quality management by explicitly incorporating procurement (MM) and financial-control (FI/CO) functions, including supplier-quality management, cost-of-poor-quality tracking and quality-linked payment governance. An illustrative project scenario and sensitivity analysis are used to demonstrate the application of the proposed KPI and evaluation structure. By treating integration as the primary design objective, the framework provides a foundation for enterprise-wide digital quality management, lifecycle information continuity and digital-twin readiness in mega construction projects. The contribution itself is evaluated through an illustrative Design Science Research demonstration and an assumption-bounded sensitivity analysis rather than through field data, with future empirical validation specified through a controlled before-and-after case-study protocol.