From Paper Production to Traction Motors: Transfer Patterns for the FOREST Digital Twin Framework

The paper industry is highly energy intensive and exposed to volatile energy markets and strict decarbonisation targets. Digital twins can couple operational data with engineering and simulation models for energy and CO2eq management, yet many solutions remain domain-specific. This paper summarises FOREST (Framework for Resource, Energy, and Sustainability Treatment) as a modular digital twin framework that integrates plant data, Asset Administration Shell (AAS)-based models, and executable simulations to provide consistent energy and material flow views, time- and product-resolved CO2eq indicators, and scenario evaluations. Based on an industrial tissue implementation, three domain-independent architectural patterns are derived. flow and state tracking, asset-centric semantics, and co-execution of models and services. These patterns are conceptually mapped to electric traction motor manufacturing and End-of-Use (EoU) testing within industrial data spaces, illustrating how plant-level optimisation logic can be extended towards lifecycle-oriented decisions on value-retention strategies.