Forza Silicon Applies Machine Learning to Production Yield Improvement

BusinessWire: Forza Silicon CTO, Daniel Van Blerkom, is to present a paper titled “Accelerated Image Sensor Production Using Machine Learning and Data Analytics” at Image Sensors Europe 2018 in London on March 15, 2018.

The machine learning has been applied to sensor data sets to identify and measure critical yield limiting defects. “Image sensors offer the unique opportunity to image the yield limiting defect mechanisms in silicon,” said Daniel Van Blerkom. “By applying machine learning to image sensor test procedures we’re able to quickly and easily classify sensor defects, identify root-cause and feedback the results to improve the process, manufacturing flow and sensor design for our clients.”