Quality assurance in wafer, cell, and module production hinges on efficient characterization processes. Precise measurements and identification of defective products are crucial for cost savings. Characterization enhances throughput and facilitate sorting based on performance metrics, making advancements in software and automation solutions imperative. Machine learning and digitalization play key roles in bolstering the robustness and efficiency of production lines and are widely adopted within the industry. In this session, companies will provide the latest advancements in the realm, while others will showcase how they track the quality of their products. The topic of quality assurance through tracked metrology will be discussed.
01:00 pm - 01:15 pmHigh Speed Cell and Module Quality Inspection Based on Electroluminescence Imaging and AI Optimized Algorithms
Mr. Matthias Krinke, Geschäftsführender Gesellschafter, pi4 robotics GmbH
01:15 pm - 01:30 pmInnovative Device Characterization Solutions
Klaus Ramspeck, Director R&D, halm elektronik GmbH
01:30 pm - 01:45 pmIV-Testing and Tandem/Perovskite: Scaling up from Cell Level to Full Size Module Production
01:45 pm - 02:00 pmVDMA China in a Nutshell
Mr. Han Chen, Project Manager, German Mechanical Engineering Commercial Services (Beijing)
02:00 pm - 02:15 pmDeep Learning Defect Detection
02:15 pm - 02:30 pmInnovations for R&D and End-of-Line Testing
Mr. Bernhard Mitchell, Lead Innovation Management, WAVELABS Solar Metrology Systems GmbH
02:30 pm - 02:45 pmLUMI-Q: The New System Platform for Photoluminescence Inspections in Cell and Module Manufacturing
Mr. Peter Handschack, VP Business Unit Solar, ISRA VISION GmbH