Monitoring the coefficient of variation using a variable sampling interval ewma chart

W. C. Yeong; Michael B.C. Khoo; L. K. Tham; W. L. Teoh; M. A. Rahim

doi:10.1080/00224065.2017.11918004

Monitoring the coefficient of variation using a variable sampling interval ewma chart

W. C. Yeong, Michael B.C. Khoo, L. K. Tham, W. L. Teoh, M. A. Rahim

School of Mathematical & Computer Sciences

Research output: Contribution to journal › Article › peer-review

60 Citations (Scopus)

Abstract

In recent years, the coefficient of variation (CV) chart is receiving increasing attention in quality control. A number of studies demonstrated that adaptive charts could detect process shifts faster than traditional charts. This paper proposes an EWMA chart with variable sampling interval (VSI) to monitor the CV. Formulas for computing the performance measures of the VSI EWMA-γ^2; chart are derived using Markov chain, where γ² denotes the CV squared. Comparative studies show that the VSI EWMA-γ² chart significantly outperforms other competing charts. An example using real manufacturing data shows that the VSI EWMA-γ² chart performs well in applications.

Original language	English
Pages (from-to)	380-401
Number of pages	22
Journal	Journal of Quality Technology
Volume	49
Issue number	4
DOIs	https://doi.org/10.1080/00224065.2017.11918004
Publication status	Published - 21 Nov 2017

Keywords

Average Time to Signal
Expected Average Time to Signal
Exponentially Weighted Moving Average Chart
Markov Chain

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Strategy and Management
Management Science and Operations Research
Industrial and Manufacturing Engineering

Access to Document

10.1080/00224065.2017.11918004

Download pdf
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Quality Technology on 21/11/2017, available at: https://doi.org/10.1080/00224065.2017.11918004
Accepted author manuscript, 891 KBLicence: CC BY-NC-ND

Cite this

@article{d2983aea1d1f40a5afa023d900e35efb,

title = "Monitoring the coefficient of variation using a variable sampling interval ewma chart",

abstract = "In recent years, the coefficient of variation (CV) chart is receiving increasing attention in quality control. A number of studies demonstrated that adaptive charts could detect process shifts faster than traditional charts. This paper proposes an EWMA chart with variable sampling interval (VSI) to monitor the CV. Formulas for computing the performance measures of the VSI EWMA-γ2; chart are derived using Markov chain, where γ2 denotes the CV squared. Comparative studies show that the VSI EWMA-γ2 chart significantly outperforms other competing charts. An example using real manufacturing data shows that the VSI EWMA-γ2 chart performs well in applications.",

keywords = "Average Time to Signal, Expected Average Time to Signal, Exponentially Weighted Moving Average Chart, Markov Chain",

author = "Yeong, {W. C.} and Khoo, {Michael B.C.} and Tham, {L. K.} and Teoh, {W. L.} and Rahim, {M. A.}",

year = "2017",

month = nov,

day = "21",

doi = "10.1080/00224065.2017.11918004",

language = "English",

volume = "49",

pages = "380--401",

journal = "Journal of Quality Technology",

issn = "0022-4065",

publisher = "Taylor & Francis",

number = "4",

}

TY - JOUR

T1 - Monitoring the coefficient of variation using a variable sampling interval ewma chart

AU - Yeong, W. C.

AU - Khoo, Michael B.C.

AU - Tham, L. K.

AU - Teoh, W. L.

AU - Rahim, M. A.

PY - 2017/11/21

Y1 - 2017/11/21

N2 - In recent years, the coefficient of variation (CV) chart is receiving increasing attention in quality control. A number of studies demonstrated that adaptive charts could detect process shifts faster than traditional charts. This paper proposes an EWMA chart with variable sampling interval (VSI) to monitor the CV. Formulas for computing the performance measures of the VSI EWMA-γ2; chart are derived using Markov chain, where γ2 denotes the CV squared. Comparative studies show that the VSI EWMA-γ2 chart significantly outperforms other competing charts. An example using real manufacturing data shows that the VSI EWMA-γ2 chart performs well in applications.

AB - In recent years, the coefficient of variation (CV) chart is receiving increasing attention in quality control. A number of studies demonstrated that adaptive charts could detect process shifts faster than traditional charts. This paper proposes an EWMA chart with variable sampling interval (VSI) to monitor the CV. Formulas for computing the performance measures of the VSI EWMA-γ2; chart are derived using Markov chain, where γ2 denotes the CV squared. Comparative studies show that the VSI EWMA-γ2 chart significantly outperforms other competing charts. An example using real manufacturing data shows that the VSI EWMA-γ2 chart performs well in applications.

KW - Average Time to Signal

KW - Expected Average Time to Signal

KW - Exponentially Weighted Moving Average Chart

KW - Markov Chain

UR - http://www.scopus.com/inward/record.url?scp=85031130036&partnerID=8YFLogxK

U2 - 10.1080/00224065.2017.11918004

DO - 10.1080/00224065.2017.11918004

M3 - Article

AN - SCOPUS:85031130036

SN - 0022-4065

VL - 49

SP - 380

EP - 401

JO - Journal of Quality Technology

JF - Journal of Quality Technology

IS - 4

ER -

Monitoring the coefficient of variation using a variable sampling interval ewma chart

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this