Abstract
The road to carbon neutrality requires a massive scale up of battery manufacturing on a rapid timescale. Li ion batteries are complex systems with many materials and interfaces, and the challenge of controlling microcale material properties of millions of units per year demands a physics and a data driven approach to manufacturing. Conversely, the Toyota Production System (TPS) for manufacturing is a deeply human-led process, thus, we have a need to integrate a variety of models with human expertise and experience. We will present our manufacturing optimization experience and approach with safety and cost as target metrics. Economics incorporates both cost of production (including yield and throughput) as well as future performance (reliability). We will present several case studies of the complexities of implementing ML for complex manufacturing problems, with emphasis on the role of inspection and safety. Finally, we will place advanced manufacturing in the context of the entire battery life cycle from materials to use, and draw on these case studies to present a vision of both data- and human-driven process improvements for battery manufacturing. Key area will focus on defect detection, root cause analysis using production data, and rapid adoption of new chemistries and cell infrastructure.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call