Dynamic Life Cycle Assessment with Live Machining Data: An Open-Source Pipeline for the Digital Product Passport (Lessons from EU REED)

Main Presenter:    Tim Weber 

Co-Authors:   Miguel Fernández Astudillo                                               

The EU-funded Horizon project REED demonstrates the implementation of a pipeline that combines live shopfloor data with the open-source EE-MRIO database BONSAI and the sustainability engine Brightway. The resulting environmental impact indicators are integrated directly into the Digital Product Passport (DPP), introducing a high level of automation and digitalisation into established LCA workflows.

REED aims to transform the manufacturing of large and complex parts in the capital goods industry through data-driven production concepts. Conventional LCA approaches in this sector rely on static inventories and periodic updates, which limits their usefulness for operational decision-making and real-time product footprint reporting. REED addresses this gap by exploring open-access solutions for building automated and transparent LCA infrastructures that enable continuous environmental monitoring and robust product-level traceability.

A key component of the project is the application of the novel EE-MRIO background database BONSAI. Published in June 2025 and developed under the Getting the Data Right initiative, BONSAI is continuously expanded using AI-assisted workflows that incorporate newly released statistical data as soon as it becomes available. Combined with the open-source sustainability engine Brightway 2.5 and close collaboration with industrial partners, the project successfully demonstrates that seamless and automated generation of environmental impact information that incorporates shopfloor-level data and exports it into DPP structures is technically feasible and ready for application in manufacturing organisations.

The use of open-source tooling significantly reduces integration barriers, improves transparency across organisational boundaries, and enables the structured export of impact indicators into DPP-compatible data models. Overall, the results represent substantial progress in LCA automation, data quality, and digital integration, and illustrate how life cycle thinking can be embedded directly into operational manufacturing systems.

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