Output details
13 - Electrical and Electronic Engineering, Metallurgy and Materials
Queen's University Belfast
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Article title
Max separation clustering for feature extraction from Optical Emission Spectroscopy Data
Type
D - Journal article
Title of journal
IEEE Transactions on Semiconductor Manufacturing
Article number
-
Volume number
24
Issue number
4
First page of article
480
ISSN of journal
0894-6507
Year of publication
2011
URL
-
Number of additional authors
1
Additional information
This paper describes a novel clustering algorithm for identifying distinctive features in correlated high-dimensional data sets. The algorithm is targeted at optical emission spectroscopy (OES) data from plasma etch processes used in the semiconductor industry as a means of summarising the dominant patterns which may serve as signatures for process monitoring and control applications. Following a successful pilot, Intel who co-sponsored the research with Enterprise Ireland, have licensed a software application incorporating the algorithm and this is currently being deployed in its fabrication facilities worldwide, Intel (Resracher in residence).
Interdisciplinary
-
Cross-referral requested
-
Research group
C - Energy, Power and Intelligent Control (EPIC)
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
