<img src=https://nenpower.com/wp-content/uploads/2025/04/image-7908.webp alt=’What role does AI play in the PV Circulator’s material separation process’ />
The PV Circulator employs AI in a key role to enhance its solar panel material separation process. Specifically, it integrates advanced vision AI and machine learning technologies to automate and optimize the recycling workflow:
- AI Vision and Machine Learning for Component Recognition: The system uses AI-powered vision technology to scan solar panels and identify their make and model by referencing a company database. It also recognizes the form factors of various PV panel components, such as aluminum frames, junction boxes, glass, backsheets, encapsulants, silicon cells, and metals, allowing for precise, automated adjustments during disassembly and sorting without human intervention.
- Neural Network Sharing for Process Optimization: All PV Circulator units are interconnected through a neural network that shares learned experiences and optimizations across machines. This prevents duplication of machine learning processes and continuously improves sorting accuracy and operational efficiency.
- Layered Material Separation Enhanced by AI: After mechanical disassembly, the panel materials are milled by layer and cooled by airflow to prevent chemical reactions. The airflow process separates and collects different materials—backsheets, encapsulants, and cell materials—while preserving the semiconductor and conductive properties of silicon and metals. This precision is enabled by AI-driven adjustments ensuring material purity for subsequent processing stages such as electrostatic separation.
- Continuous Process Optimization: The autonomous machine learning capabilities embedded in the PV Circulator continuously optimize the recycling process, improving activation rates and system performance over time. This adaptive learning enables the equipment to handle varying panel types and configurations efficiently.
- Automated Data and Traceability: The system functions as an Internet of Things (IoT) device, generating immutable, clean recycling records for each panel processed. This data is automatically uploaded to secure blockchain-based (Web3) platforms, enhancing transparency and traceability in the recycling chain.
In summary, AI in the PV Circulator fundamentally drives automated, precise, and optimized material separation by enabling smart recognition, adaptive operation, shared learning, and data transparency. This results in highly efficient, low-waste recycling of solar panels, supporting circular economy goals in photovoltaic material recovery.
Original article by NenPower, If reposted, please credit the source: https://nenpower.com/blog/what-role-does-ai-play-in-the-pv-circulators-material-separation-process/
