Wafer Plot Classification Using Neural Networks and Tensor Methods

Ahmed Wahba, Chuanhe Jay Shan, Li-C. Wang, Nik Sumikawa

Abstract: This paper presents an automated flow to classify wafer plots obtained based on production test data. The wafer plots are based on pass/fail locations. The classification is achieved through wafer pattern recognition models built with two sets of techniques, Generative Adversarial Networks and Tensor analysis. The primary focus is on developing the automatic flow. Experiment results based on production test data from a microcontroller product line will be presented to demonstrate the usefulness of the proposed classification flow.