HxGN Visual Detection can be deployed to support a wide range of use cases. It can manage high-speed throughput within a large manufacturing cell or when checking small numbers of high-value components during a proof of concept. HxGN Visual Detection uses CNN (convolutional neural network) deep learning models to train, identify and categorize surface defects.

Ready for use with Hexagon’s Optiv vision CMMs, HxGN Visual Detection can easily be incorporated into metrology workflows with PC-DMIS Vision to add surface inspection. The fully automated, one-shot measurement and defect detection approach will increase autonomy and accuracy and improve efficiency in any workflow.