Quality assurance in the production of optical lenses is a time-consuming, largely manual process. This is inefficient and also highly prone to errors, which can lead to incorrect quantities and delivery delays. Due to the high demands of the processing industry, efficient and precise quality assurance is a decisive factor for competitiveness. Previous methods for automated defect detection are either too expensive, too time-consuming or not precise enough to identify specific defect types and optimize the production process.

ALQUA combines an AI-supported system for visual defect analysis with direct feedback to adjust production parameters. This holistic system, consisting of ALQUA-QS and ALQUA-Control, enables automated, precise defect detection and process optimization, which is not yet available on the market.

A high-resolution digital microscope is used, which is combined with artificial intelligence methods, including deep learning models. This combination of technologies will enable precise defect detection and classification. In addition, a reinforcement learning approach is used to optimize process parameters in order to improve the manufacture of new products.