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

49 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

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10.1080/00224065.2017.11918004

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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.",

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AU - Tham, L. K.

AU - Teoh, W. L.

AU - Rahim, M. A.

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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.

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KW - Expected Average Time to Signal

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

Abstract

Keywords

ASJC Scopus subject areas

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