Quality assurance through defect detection in solar cell production

Challenges

Today, inspections to find faults in photovoltaic panel production are still carried out manually by a worker on site.

In order to simplify this process and to reduce the error rate, elunic was commissioned to develop a system based on artificial intelligence that automatically detects errors.

Key Features

• Increase of quality and reduction of rejects during the production process.
• Increase of throughput through automation.
• Reduction of costs.

Solutions & Services

• Use of deep learning algorithms for error detection.
• Labeling and classifying of custom errors.
• Installation of required hardware.
• MES and quality management integration.