Conceptualizing a Digital Twin Architecture for Enhanced Control in Precast Concrete Production

This paper proposes a novel Digital Twin (DT) architecture tailored for the precast concrete manufacturing process, focusing on optimizing temperature and moisture control during curing. By integrating a detailed case study from a leading construction company in Melbourne, Australia, the study outlines the application of advanced IoT sensors, machine learning algorithms, and simulation technologies to improve operational efficiencies and ensure product compliance with industry standards. The architecture is designed to provide real-time insights and proactive adjustments, enhancing the quality and sustainability of precast concrete products. This research contributes to the digital transformation of construction practices by offering a scalable and precise DT framework that supports the entire lifecycle of precast concrete elements.