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Process control of time-varying systems using parameter-less self-organizing maps

Authors
Choung, Young JaeKang, JihoonKim, Seoung Bum
Issue Date
Apr-2017
Publisher
ELSEVIER SCI LTD
Keywords
Multivariate process control; Control chart; Self-organizing map; Time-varying process; Data mining; Machine learning
Citation
JOURNAL OF PROCESS CONTROL, v.52, pp.45 - 56
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF PROCESS CONTROL
Volume
52
Start Page
45
End Page
56
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/83802
DOI
10.1016/j.jprocont.2017.02.005
ISSN
0959-1524
Abstract
Traditional control charts, such as Hotelling's T-2, are effective in detecting abnormal patterns. However, most control charts do not take into account a time-varying property in a process. In the present study, we propose a parameter-less self-organizing map-based control chart that can handle a situation in which changes occur in the distribution or parameter of the target observations. The control limits of the proposed chart are determined by estimating the empirical level of significance on the percentile using the bootstrap method. Experimental results obtained by using simulated data and actual process data from the manufacturing process for a thin-film transistor-liquid crystal display demonstrate the effectiveness and usefulness of the proposed algorithm. (C) 2017 Elsevier Ltd. All rights reserved.
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