Whitepaper of the RWTH Aachen
AI Makes Battery Production Significantly More Efficient
The PEM Chair at RWTH Aachen University has explored the potential of AI in battery production with partners from industry. They explain the results in an English-language white paper, which is now available for download free of charge.
In the new 20-page white paper, the authors explore the possibilities of real-time data processing to maximise quality, output and efficiency in battery manufacturing. The authors look at three promising use cases: automated root cause analysis, proactive efficiency improvement and the machine condition index.
»Mastering the available data and analysing it in real time is crucial for sustainable, successful battery production,« explains the head of the »Chair of Production Engineering of E-Mobility Components« (PEM) at RWTH Aachen University, Professor Achim Kampker.
Therefore, the white paper evaluates all the advantages of the examined use cases specifically for battery production and shows current solutions from the software developers CamLine and Elisa IndustrIQ for increasing efficiency. The authors then define an initial procedure for implementing artificial intelligence and machine learning solutions in other companies.
»Real-time data analytics, combined with remediation of deviations, can significantly improve battery production, thereby significantly increasing profitability and quality in addition to sustainability,« says Kampker.
The white paper »Maximising Efficiency: Navigating the Gigafactory Journey with Real-Time Data Insights« is available as a free download.
