A data mining approach to improve phase I process control

Chang W. Kang; Thuntee Sukchotrat; Seoung Bum Kim

A data mining approach to improve phase I process control

Chang W. Kang, Thuntee Sukchotrat, Seoung Bum Kim

Research output: Contribution to conference › Paper › peer-review

Abstract

We propose a data mining approach to improve the phase I analysis of statistical process control. We use the clustering analysis to make initial groups of the historical data, followed by the classification analysis, along with the synthetic datasets to further purify the in-control data. The simulation study shows that our proposed approach performs better than a traditional control chart technique.

Original language	English
Pages	192-196
Number of pages	5
Publication status	Published - 2007
Externally published	Yes
Event	IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Nashville, TN, United States Duration: 2007 May 19 → 2007 May 23

Other

Other	IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World
Country/Territory	United States
City	Nashville, TN
Period	07/5/19 → 07/5/23

Keywords

Classification analysis
Clustering analysis
Data mining
Multivariate control chart
Phase I analysis

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Cite this

@conference{e14896b9f7ad4194a5f17c550cbfc736,

title = "A data mining approach to improve phase I process control",

abstract = "We propose a data mining approach to improve the phase I analysis of statistical process control. We use the clustering analysis to make initial groups of the historical data, followed by the classification analysis, along with the synthetic datasets to further purify the in-control data. The simulation study shows that our proposed approach performs better than a traditional control chart technique.",

keywords = "Classification analysis, Clustering analysis, Data mining, Multivariate control chart, Phase I analysis",

author = "Kang, {Chang W.} and Thuntee Sukchotrat and Kim, {Seoung Bum}",

year = "2007",

language = "English",

pages = "192--196",

note = "IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World ; Conference date: 19-05-2007 Through 23-05-2007",

}

TY - CONF

T1 - A data mining approach to improve phase I process control

AU - Kang, Chang W.

AU - Sukchotrat, Thuntee

AU - Kim, Seoung Bum

PY - 2007

Y1 - 2007

N2 - We propose a data mining approach to improve the phase I analysis of statistical process control. We use the clustering analysis to make initial groups of the historical data, followed by the classification analysis, along with the synthetic datasets to further purify the in-control data. The simulation study shows that our proposed approach performs better than a traditional control chart technique.

AB - We propose a data mining approach to improve the phase I analysis of statistical process control. We use the clustering analysis to make initial groups of the historical data, followed by the classification analysis, along with the synthetic datasets to further purify the in-control data. The simulation study shows that our proposed approach performs better than a traditional control chart technique.

KW - Classification analysis

KW - Clustering analysis

KW - Data mining

KW - Multivariate control chart

KW - Phase I analysis

UR - http://www.scopus.com/inward/record.url?scp=44949186446&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:44949186446

SP - 192

EP - 196

T2 - IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World

Y2 - 19 May 2007 through 23 May 2007

ER -

A data mining approach to improve phase I process control

Abstract

Other

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this