Anomaly detection to implement products during lifetime testing on Xilinx ZynqMP SoC-based edge AI-supported environment

An essential part of semiconductor manufacturing during development projects is the ability to measure the finished products to compare the development project’s technical objectives with the given development sample parameters. Reducing the time available for development and, thus, the number of simultaneous development projects present at the same time requires the measurement of the rapid processing of the measured data at the point of origin and using the resulting information to make decisions.
The student is expected to learn about the HW (Xilinx ZynqMP SoC-based edge AI) and SW (HADOOP / Tensorflow, etc.) environment and, based on this knowledge, explore the Xilinx ZynqMP SoC-based edge AI and the sensor development opportunities that are expected to require edge AI solutions. The student should be able to help make decisions that will determine the future direction of development.