This webinar explores how machine vision for EV batteries supports next-generation quality control.
The growing market for electric vehicles is driving demand for different battery technologies. While each battery is designed to meet the specific needs of an application, all batteries must be lightweight and compact, have a long life both in use and in storage, and deliver a relatively consistent voltage during operation. While these goals can be achieved in numerous ways using different battery technologies, materials, and processes, many battery designs meet these demanding performance requirements using multi-layer structures. Detecting even small deviations in the surface structure before the battery is installed is crucial for EV battery inspection and overall quality assurance. Machine vision for EV batteries enables manufacturers to catch these defects early and ensure long-term performance.
Join Dr. Thomas Reitberger, Product Leader, at Micro-Epsilon and Carl Lewis, Sr. Director of Partnerships at LandingAI to learn more:
- Real-world use case using AI in EV battery manufacturing
- How AI and domain-specific Large Vision Models can further improve inspection accuracy and speed to production
- Live Q&A
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