A Construction-Phase Digital Twin for Proactive Quality Assurance and Element-Level Decision Support in Civil Infrastructure

Abstract

Quality assurance (QA) in civil infrastructure construction remains largely reactive, relying on inspection records and laboratory test results that become available days or weeks after work completion. This latency precludes timely intervention, leading to rework, schedule delays, and fragmented documentation. While digital twins have been explored for construction, current implementations predominantly focus on information aggregation, monitoring, and visualization, lacking the continuous data integration and operational decision logic needed for proactive, systematic QA. To address this gap, this paper presents a construction-phase digital twin designed for proactive QA and element-level decision support. The framework continuously integrates inspection records, material production and placement data, early-age sensing, and predictive strength models—all linked to individual construction elements. This integration enables two key advancements: (1) real-time representation of each element's evolving quality state, and (2) structured release-or-hold decisions before standard-age test results become available. The result is a shift from delayed, document-centric QA reviews to timely, data-driven assessments that enhance traceability and reduce rework risk, without supplanting established testing procedures. Practical considerations regarding data integration, contractual constraints, and implementation challenges are also discussed, providing a structured pathway for transitioning construction QA from reactive compliance checking to proactive, element-level decision support.