Wood-for-construction supply chain digital twin to drive circular economy and actor-based LCA information

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Abstract

The integration of Digital Twin (DT) technologies and Life Cycle Assessment (LCA) in the construction sector presents significant opportunities for improving resource efficiency, enhancing material traceability, and supporting circular economy strategies. However, the lack of standardized methodologies and data interoperability remains a major barrier to effective implementation. This study introduces the Forest to Building Digital Framework (F2BDF), a structured approach that combines DT technologies, actor-based LCA, and supply chain management digital tools to optimize the environmental performance of wood construction. The research is among the earliest to develop a digital system throughout the life cycle from the extraction of raw materials to the construction. The framework is built on a hierarchical structure where digitalized different actors’ subsystems within the supply chain generate real-time production data, feeding into a centralized backbone network. These data are the foundation for a decision support module designed to assess environmental impacts and evaluate circularity scenarios. The study integrates geospatial analysis (GIS), real-time manufacturing data (CAx and BIM), and digital product information. The validation process in an industrial setting exhibits how enhanced data integration can support real-time sustainability assessments with primary foreground data and optimize resource utilization. The results included enhanced material circularity options, data portability, and building materials tracking, as well as semi-automatically contributing to achieving more dynamic and actor-based LCA information. By digitizing multiple stakeholders and making product, production, and transportation data accessible via APIs (Application Programming Interfaces), widespread digital frameworks can offer a scalable solution for improving sustainability across the wood construction sector.

Original languageEnglish
Article number146074
JournalJournal of Cleaner Production
Volume520
DOIs
Publication statusPublished - 15 Aug 2025

Keywords

  • Dynamic environmental product declaration
  • Life cycle assessment
  • Semantic data models
  • Smart manufacturing industry
  • Supply chain digital twin

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