Automatic semiconductor wafer map defect signature detection using a neural network classifier

Repository

Automatic semiconductor wafer map defect signature detection using a neural network classifier

Show full record

Title: Automatic semiconductor wafer map defect signature detection using a neural network classifier
Author: Radhamohan, Ranjan Subbaraya
Abstract: The application of popular image processing and classification algorithms, including agglomerative clustering and neural networks, is explored for the purpose of grouping semiconductor wafer defect map patterns. Challenges such as overlapping pattern separation, wafer rotation, and false data removal are examined and solutions proposed. After grouping, wafer processing history is used to automatically determine the most likely source of the issue. Results are provided that indicate these methods hold promise for wafer analysis applications.
Department: Electrical and Computer Engineering
Subject: Semiconductor Wafer Neural Network Agglomerative Clustering Map Defect Yield
URI: http://hdl.handle.net/2152/ETD-UT-2010-12-2423
Date: 2010-12

Files in this work

Size: 1.255Mb
Format: application/pdf

This work appears in the following Collection(s)

Show full record


Advanced Search

Browse

My Account

Statistics

Information