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Nobleo brings intelligent deep learning solutions to MEKOPP

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Founded in 2011, Nobleo Technology has since grown to over 75 employees and offers expertise on the development of mechatronics design solutions, autonomous robotics and machine learning algorithms for high-tech applications. The latter brought them to the MEKOPP project, where they are responsible for the software that detects wafer defects on photonic wafers (PICs) with a step-and-scan microscope. The tool can process a 20-megapixel image in 100 milliseconds, targeting a throughput rate of 10 wafers per second (4 inch). The microscope generates PIC images with an image resolution of 0.3 μm and/or 0.1 μm.

Within the MEKOPP project, Nobleo developed a machine learning suite that facilitates automation of the visual inspection task. The operator can categorise the defects found according to company-specific categories in order to build up a database of defect images. The tool is fully web-based, thereby allowing anybody anywhere to assess the images taken. Once a consistent definition of a defect category is established, a machine learning algorithm is trained to automate the inspection task.

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The MEKOPP project is funded by:

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