A novel Zero-Defect Manufacturing approach for defect reduction in battery production
Li-ion batteries are fundamental components for the energy transition of the European ecosystem. Currently, Europe lags behind Asia in terms of Li-ion battery cell manufacturing, over 90% of the world’s production takes place in Far East. To overcome this situation, there is an ambitious ramp-up plan of 25 new gigafactories in Europe with an expected value of €35 bn by 2030. However, during the ramp-up phase it is expected that a significant amount of deffective batteries and scrap, estimated between 15%-30%, will be generated due to the lack of knowledge-based methods for production quality improvement in the battery sector. This paper presents the innovative features of the Zero-Defect Manufacturing approach for battery production lines proposed by the BATTwin project. The solution encompasses four interconnected layers: (i) a multi-sensor data acquisition and management layer, supported by data semantics through a Digital Battery Passport compliant data model; (ii) process-level digital twins, modeling the critical stages of electrode manufacturing, cell assembly and conditioning through multi-physics, data-driven and hybrid approaches; (iii) system-level models, based on simulation and analytical modeling; (iv) user-centric, goal-driven workflows, increasing the explainability of digital twins and driving the user in system design and control. The current progress of the proposed approach and the future validation plan to meet target KPIs are discussed for two industrial pilots producing different battery chemistries and geometries, demonstrating the flexibility and scalability of the approach towards Zero-Defect European Gigafactories.
Authors
- Gergely Horváth (ORCID: https://orcid.org/0000-0003-2873-4594)
- Marcello Colledani (ORCID: https://orcid.org/0000-0002-9312-6643)
- Ozan Demir (ORCID: https://orcid.org/0000-0002-4484-5051)
- Donia Marzogui
- Konstantina Giakoumi
Institutions
- nLIGHT (United States) (US)
- HUN-REN Institute for Computer Science and Control (HU)
- Verimag (FR)
- Politecnico di Milano (IT)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.02.256
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- HORIZON EUROPE Framework Programme