Enhancing Traceability in Battery Cell Production Through the Implementation of a Standardized Information Model

The growing demand for electric vehicles requires highly efficient, transparent, and data-driven battery cell production processes. Traceability (TR) plays a central role in ensuring product quality, supporting process optimization, and meeting regulatory requirements, particularly in the context of the emerging battery passport. However, existing TR solutions are often fragmented and tightly coupled to specific equipment, limiting cross-system interoperability and scalability. This paper presents an architecture for traceability in battery cell production based on an OPC UA information model. The model enables machine-independent semantic structuring of production data and supports consistent interpretation across heterogeneous manufacturing environments. It forms the foundation for scalable TR systems that can be flexibly applied across real and simulated processes, and across both continuous and discrete manufacturing steps. We demonstrate the integration of this information model into an existing traceability system (FFTrace), using a hybrid process chain that combines a real-world calendering process with a simulated slitting process. ... mehrThe focus is on asynchronous data processing, with real machine data mapped to model-compliant structures and imported via an Information Model Adapter. Traceability events are semantically defined, detected, and linked to product instances across process boundaries. The results confirm that using a standardized information model decouples data acquisition from system logic, reduces integration effort, and enables consistent material tracking across different systems. The architecture supports future extensions toward real-time applications and advanced use cases such as defect analysis, digital product passports, and full-process-chain traceability. This research paper contributes to developing interoperable Industry 4.0 solutions in battery manufacturing and demonstrates how semantic information modelling enables robust, scalable, and future-proof traceability implementations.