The goal of the project is to develop an innovative, AI-based thermographic-optical multisensor system for the reliable detection of surface and volumetric defects in the production of electrodes for lithium-ion batteries. Through the intelligent combination of active thermography and optical imaging, defects are to be identified early, precisely, and in real time.
Both physical and digitally synthesized defect samples are being developed and used to ensure robust validation of the system. For the first time, the methodology outlined in VDA Volume 5.3 is being applied to validate an AI-based multimodal imaging system in the electrode manufacturing of lithium-ion batteries. This sets a new standard for the validation of intelligent quality assurance systems in battery cell production.
OptiSense is contributing its many years of expertise in the field of active thermography to the project. The focus is not only on determining coating thickness, but also on developing a high-performance thermographic imaging system for real-time defect detection and analysis throughout the entire manufacturing process.
The intelligent integration of active thermography with optical inspection methods and AI-supported real-time analysis enables comprehensive process monitoring. This allows even hidden material and manufacturing defects to be detected early on, production processes to be optimized in a targeted manner, and the quality and efficiency of battery cell manufacturing to be sustainably improved—far beyond the capabilities of simple coating thickness measurement.
Project Overview
- Project Management Agency: Projektträger Jülich (PtJ)
- Funding Agency: Industrie.IN.NRW
- Grant Number: EFRE-20801409
- Duration: 01.01.2026 – 31.12.2028