Title :
Two dimensional curve shape primitives for detecting line defects in silicon wafers
Author :
Sikka, Digvijay L.
Author_Institution :
Intel Corp., Santa Clara, CA, USA
Abstract :
A new set of two-dimensional curve shape primitives for detecting line defects on wafers in semiconductor manufacturing is presented. A supervised learning based neural network which incorporates these shape primitives has been built and tested on more than six months of real data from an Intel fabrication laboratory. Results demonstrate that the new set of shape primitives was very accurate in capturing the line defects
Keywords :
learning (artificial intelligence); pattern recognition; semiconductor device manufacture; 2D curve shape primitives; line defects detection; semiconductor manufacturing; silicon wafers; supervised learning based neural network; Artificial intelligence; Artificial neural networks; Image edge detection; Intelligent networks; Manufacturing automation; Neural networks; Semiconductor device manufacture; Shape; Silicon; Supervised learning;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227110
