New architecture and systems for wafer inspection are developed.


IFAG, Symate

The demonstrator provides an optical inspection solution working on the same or similar hardware and software environment. The demonstrator consists of several phases:

  • (Pseudo-)anomaly detection with a pre-trained neural network (NN) for detecting deviations
  • A pool of labelled images is generated for a supervised approach to build a classifier model by checking those deviations
  • Deploying this model to unseen productive images and analysing the predictions which provide information about the target performance

Beyond state-of-the-art developments and impacts

The approach is innovative in making a two-step process by firstly using some unsupervised trained anomaly detection and secondly analysing (and with this step labelling) deviating data (e.g., images). With these data, a supervised training for generating a model is conducted, which can predict more information. This can be a blueprint on dealing with a lack of labelled data when starting an AI project.