Battery cell production is a highly complex process shaped by numerous parameters, tight tolerances, and varying material properties. Even small deviations can have a significant impact on quality, lifetime, and cost. Traditional optimization methods often reach their limits in managing this complexity. Artificial Intelligence provides new possibilities by uncovering patterns in large datasets, modeling process steps, and generating actionable insights. This not only enhances quality assurance but also accelerates the development of innovative production strategies.

Join this session and learn more about:

• Insights into data-driven modeling approaches for process optimization
• Application of AI methods to prevent defects and improve product quality
• Strategies to integrate AI models into existing production environments