A new approach to detecting the process changes for multistage systems

Jeh-Nan Pan, Chung-I Li, Jhe Jia Wu

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The study aims to develop a new control chart model suitable for monitoring the process quality of multistage manufacturing systems. Considering both the auto-correlated process outputs and the correlation occurring between neighboring stages in a multistage manufacturing system, we first propose a new multiple linear regression model to describe their relationship. Then, the multistage residual EWMA and CUSUM control charts are used to monitor the overall process quality of multistage systems. Moreover, an overall run length (ORL) concept is adopted to compare the detecting performance for various multistage residual control charts. Finally, a numerical example with oxide thickness measurements of a three-stage silicon wafer manufacturing process is given to demonstrate the usefulness of our proposed multistage residual control charts in the Phase II monitoring. A computerized algorithm can also be written based on our proposed scheme for the multistage residual EWMA/CUSUM control charts and it may be further converted to an expert and intelligent system. Hopefully, the results of this study can provide a better alternative for detecting process change and serve as a useful guideline for quality practitioners when monitoring and controlling the process quality of multistage systems with auto-correlated data.

Original languageEnglish
Pages (from-to)293-301
Number of pages9
JournalExpert Systems With Applications
Volume62
DOIs
Publication statusPublished - 2016 Nov 15

Fingerprint

Monitoring
Thickness measurement
Intelligent systems
Silicon wafers
Linear regression
Expert systems
Control charts
Oxides

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Cite this

@article{94cdfb7b8fd5464f9066e11eb507291f,
title = "A new approach to detecting the process changes for multistage systems",
abstract = "The study aims to develop a new control chart model suitable for monitoring the process quality of multistage manufacturing systems. Considering both the auto-correlated process outputs and the correlation occurring between neighboring stages in a multistage manufacturing system, we first propose a new multiple linear regression model to describe their relationship. Then, the multistage residual EWMA and CUSUM control charts are used to monitor the overall process quality of multistage systems. Moreover, an overall run length (ORL) concept is adopted to compare the detecting performance for various multistage residual control charts. Finally, a numerical example with oxide thickness measurements of a three-stage silicon wafer manufacturing process is given to demonstrate the usefulness of our proposed multistage residual control charts in the Phase II monitoring. A computerized algorithm can also be written based on our proposed scheme for the multistage residual EWMA/CUSUM control charts and it may be further converted to an expert and intelligent system. Hopefully, the results of this study can provide a better alternative for detecting process change and serve as a useful guideline for quality practitioners when monitoring and controlling the process quality of multistage systems with auto-correlated data.",
author = "Jeh-Nan Pan and Chung-I Li and Wu, {Jhe Jia}",
year = "2016",
month = "11",
day = "15",
doi = "10.1016/j.eswa.2016.06.037",
language = "English",
volume = "62",
pages = "293--301",
journal = "Expert Systems with Applications",
issn = "0957-4174",
publisher = "Elsevier Limited",

}

A new approach to detecting the process changes for multistage systems. / Pan, Jeh-Nan; Li, Chung-I; Wu, Jhe Jia.

In: Expert Systems With Applications, Vol. 62, 15.11.2016, p. 293-301.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A new approach to detecting the process changes for multistage systems

AU - Pan, Jeh-Nan

AU - Li, Chung-I

AU - Wu, Jhe Jia

PY - 2016/11/15

Y1 - 2016/11/15

N2 - The study aims to develop a new control chart model suitable for monitoring the process quality of multistage manufacturing systems. Considering both the auto-correlated process outputs and the correlation occurring between neighboring stages in a multistage manufacturing system, we first propose a new multiple linear regression model to describe their relationship. Then, the multistage residual EWMA and CUSUM control charts are used to monitor the overall process quality of multistage systems. Moreover, an overall run length (ORL) concept is adopted to compare the detecting performance for various multistage residual control charts. Finally, a numerical example with oxide thickness measurements of a three-stage silicon wafer manufacturing process is given to demonstrate the usefulness of our proposed multistage residual control charts in the Phase II monitoring. A computerized algorithm can also be written based on our proposed scheme for the multistage residual EWMA/CUSUM control charts and it may be further converted to an expert and intelligent system. Hopefully, the results of this study can provide a better alternative for detecting process change and serve as a useful guideline for quality practitioners when monitoring and controlling the process quality of multistage systems with auto-correlated data.

AB - The study aims to develop a new control chart model suitable for monitoring the process quality of multistage manufacturing systems. Considering both the auto-correlated process outputs and the correlation occurring between neighboring stages in a multistage manufacturing system, we first propose a new multiple linear regression model to describe their relationship. Then, the multistage residual EWMA and CUSUM control charts are used to monitor the overall process quality of multistage systems. Moreover, an overall run length (ORL) concept is adopted to compare the detecting performance for various multistage residual control charts. Finally, a numerical example with oxide thickness measurements of a three-stage silicon wafer manufacturing process is given to demonstrate the usefulness of our proposed multistage residual control charts in the Phase II monitoring. A computerized algorithm can also be written based on our proposed scheme for the multistage residual EWMA/CUSUM control charts and it may be further converted to an expert and intelligent system. Hopefully, the results of this study can provide a better alternative for detecting process change and serve as a useful guideline for quality practitioners when monitoring and controlling the process quality of multistage systems with auto-correlated data.

UR - http://www.scopus.com/inward/record.url?scp=84976482555&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84976482555&partnerID=8YFLogxK

U2 - 10.1016/j.eswa.2016.06.037

DO - 10.1016/j.eswa.2016.06.037

M3 - Article

VL - 62

SP - 293

EP - 301

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

ER -