Although precast concrete construction offers more efficient construction processes, it still raises environmental concerns, mainly due to the carbon footprint associated with cement production. Life Cycle Assessment (LCA) is essential to systematically assess the environmental impacts of products, processes, or activities throughout their life cycle. A significant challenge in LCA is the collection of accurate resource consumption data, which is essential for accurately quantifying environmental impacts, developing sustainability strategies, and enabling reliable and transparent assessment. Digital Twins (DTs) enable LCAs by virtually mapping the entire life cycle. DTs provide a comprehensive overview of the entire life cycle of products, services, or processes and thus can enable accurate calculation of carbon emissions at different life cycle phases. By integrating data on energy consumption, transportation, production, and other relevant factors, the carbon footprint of precast concrete products can be determined. This work aims to create a data basis for selected aspects to evaluate the resource consumption of concrete modules generated during production, transport, and assembly. For this purpose, concepts are developed to integrate statically available life cycle inventory data from Life Cycle Inventory (LCI) databases and data collected during production into a DT. A hybrid approach is created by merging data collected in real time with established LCI databases. The Asset Administration Shell (AAS) is used as the platform for the DT. Existing LCI databases are integrated via Linked Data (LD) and Semantic Mapping. A prototypical implementation is sketched, and a case study for a precast module is presented in this paper.