- Start: 01/09/2010
- End: 31/08/2013
REPTILE has development a breakthrough technique for automated defect detection and repair in PV cells. A machine learning algorithm uses image diagnostic data to identify defected areas in a cell and take decisions on the repair strategy. Laser based repair includes laser scribing based isolation to remove shunts and hotspots, and multipass laser cutting to resize the cells or remove cracks or highly defective areas. The system runs in a high yield chain which diagnoses and reclassifies the laser processed parts, using a multisection suction system and flexible automation to handle non-standard and broken PV cells..
AIMEN was the project coordinator and the main developer of the laser based repair and separation technology. Besides, AIMEN has also developed the image processing, machine learning and defect identification tool which lays in the heart of the system logic and control.
**This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 286955.
- Sectors: Energy, Photovoltaic, Renewable energies
- Financing programme: 7TH FRAMEWORK PROGRAMME FUNDED EUROPEAN RESEARCH AND TECHNOLOGICAL DEVELOPMENT
- R&D&i: Laser assisted processing
- Partners: ISC KONSTAZ, INGESEA, SOLARTEC, ENOPSYS
- Acronym: REPTILE
- Ambit: International
- Web: http://reptile-project.aimen.es
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