Digital twin-enabled visibility and traceability for building materials in on-site fit-out construction

Fit-out construction is crucial for the functionality of completed infrastructures. However, the absence of a robust data collection system hinders efficient project management, causing delays and extra costs. This paper introduces a digital twin-enabled platform that utilizes Internet of Things (IoT) and neural network technologies for real-time visibility and traceability of prefabricated materials. The effectiveness of the proposed platform has been validated through a real-life prefabricated construction project in Hong Kong. Leveraging the IoT-captured data, visual and event-driven process models are developed to simulate materials flow and workflow executions. Hierarchical finite state machines (HFSM) facilitate the management of prefabricated construction supply chain. Results show the platform's effectiveness in identifying abnormal event states and notifying stakeholders in real-time, thus supporting advanced project management practices. This platform improves information coordination among stakeholders, providing real-time visibility and traceability, and enabling hierarchical management at strategic, tactical, and operational levels throughout the prefabrication process. •A service-oriented 5D digital twin model is proposed for real-time visibility and traceability.•Event-driven virtual and real mapping are based on AutomationML and OPC UA.•The effectiveness of the proposed model is validated in a practical case study.•Hierarchical management positively influence on the performance of prefabricated fit-out construction projects.