Intelligent features that automate your inspection
An artificial intelligence analyzer you train, with as few as 10 samples, to recognize your defects of interest. Once trained, you can import the analyzer into a production tool and begin to automatically detect and classify defects.
Using the AI analyzer eliminates the need for image tagging and other tasks that you have been doing manually. This automation speeds up inspection and eliminates operator error.
The AI analyzer uses a deep learning convolutional neural network to breakdown images into a matrix of pixels and then it stores that information for future comparison to other images. Over time, the algorithm “learns”. It gets better and faster until the detection and classification is fully and reliably automated.
A device inspection feature that compares a die without defects to other dies and reports the position coordinates of all dies with defects, whether they are random defects caused by particles, or systematic defect clusters caused by conditions of the photomask and exposure process. The system then generates a defect map report of all defects detected on the wafer.