A monitoring method of semiconductor manufacturing processes usingInternet of Things-based big data analysis

Collection with item attached
2017
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/473743.do
DOI
10.1177/1550147717721810
Title
A monitoring method of semiconductor manufacturing processes usingInternet of Things-based big data analysis
abstract
This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things-based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.
provenance
Made available in Cube on 2018-09-28T10:27:41Z (GMT). No. of bitstreams: 0
language
English
author
Jang, Seok-Woo
Kim, Gye-Young
accessioned
2018-09-28T10:27:41Z
available
2018-09-28T10:27:41Z
issued
2017
citation
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS(13): 7
issn
1550-1477
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/473743.do
Funder
교육부
Funding Program
BK21플러스사업(0.5)
Project ID
1345274424
Jurisdiction
Rep.of Korea
Project Name
Software Security Program
rights
openAccess
subject
Monitoring
learning
prediction
matched pattern
Internet of Things
reference model
type
article


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