Economic and economic statistical designs for MEWMA control charts

Kevin W Linderman, Thomas E. Love

Research output: Contribution to journalArticle

62 Citations (Scopus)

Abstract

This paper proposes methods for determining the optimal choice of design parameters (including control limits, sample size, exponential weights for past observations, and sampling interval) for the multivariate exponentially weighted moving average (MEWMA) control chart. Extending the Lorenzen-Vance flexible cost model (Lorenzen and Vance (1986)) to develop economic designs for MEWMA control chart parameters, we then add statistical constraints to obtain economic statistical designs. The choice of parameters is dependent on the average run length (ARL) when the process is in control and out of control. Evaluating the ARL values for the MEWMA chart through simulation, we determine optimal chart parameters given cost information. Results are presented on model sensitivity (in terms of expected cost and out-of-control ARL) to misspecification of the size of the shift in the process mean vector. We also consider the impact of perturbing the sampling interval on expected cost.

Original languageEnglish (US)
Pages (from-to)410-417
Number of pages8
JournalJournal of Quality Technology
Volume32
Issue number4
StatePublished - Dec 1 2000

Fingerprint

Economics
Costs
Sampling
Control charts
Exponentially weighted moving average
Average run length
Charts
Sample size
Process mean
Cost model
Economic design
Simulation
Information costs
Misspecification

Keywords

  • Economic Control Charts
  • Exponentially Weighted Moving Average Control Charts
  • Multivariate Control Charts

Cite this

Economic and economic statistical designs for MEWMA control charts. / Linderman, Kevin W; Love, Thomas E.

In: Journal of Quality Technology, Vol. 32, No. 4, 01.12.2000, p. 410-417.

Research output: Contribution to journalArticle

@article{2529693e0ed5426e978c83d84d6e722d,
title = "Economic and economic statistical designs for MEWMA control charts",
abstract = "This paper proposes methods for determining the optimal choice of design parameters (including control limits, sample size, exponential weights for past observations, and sampling interval) for the multivariate exponentially weighted moving average (MEWMA) control chart. Extending the Lorenzen-Vance flexible cost model (Lorenzen and Vance (1986)) to develop economic designs for MEWMA control chart parameters, we then add statistical constraints to obtain economic statistical designs. The choice of parameters is dependent on the average run length (ARL) when the process is in control and out of control. Evaluating the ARL values for the MEWMA chart through simulation, we determine optimal chart parameters given cost information. Results are presented on model sensitivity (in terms of expected cost and out-of-control ARL) to misspecification of the size of the shift in the process mean vector. We also consider the impact of perturbing the sampling interval on expected cost.",
keywords = "Economic Control Charts, Exponentially Weighted Moving Average Control Charts, Multivariate Control Charts",
author = "Linderman, {Kevin W} and Love, {Thomas E.}",
year = "2000",
month = "12",
day = "1",
language = "English (US)",
volume = "32",
pages = "410--417",
journal = "Journal of Quality Technology",
issn = "0022-4065",
publisher = "American Society for Quality",
number = "4",

}

TY - JOUR

T1 - Economic and economic statistical designs for MEWMA control charts

AU - Linderman, Kevin W

AU - Love, Thomas E.

PY - 2000/12/1

Y1 - 2000/12/1

N2 - This paper proposes methods for determining the optimal choice of design parameters (including control limits, sample size, exponential weights for past observations, and sampling interval) for the multivariate exponentially weighted moving average (MEWMA) control chart. Extending the Lorenzen-Vance flexible cost model (Lorenzen and Vance (1986)) to develop economic designs for MEWMA control chart parameters, we then add statistical constraints to obtain economic statistical designs. The choice of parameters is dependent on the average run length (ARL) when the process is in control and out of control. Evaluating the ARL values for the MEWMA chart through simulation, we determine optimal chart parameters given cost information. Results are presented on model sensitivity (in terms of expected cost and out-of-control ARL) to misspecification of the size of the shift in the process mean vector. We also consider the impact of perturbing the sampling interval on expected cost.

AB - This paper proposes methods for determining the optimal choice of design parameters (including control limits, sample size, exponential weights for past observations, and sampling interval) for the multivariate exponentially weighted moving average (MEWMA) control chart. Extending the Lorenzen-Vance flexible cost model (Lorenzen and Vance (1986)) to develop economic designs for MEWMA control chart parameters, we then add statistical constraints to obtain economic statistical designs. The choice of parameters is dependent on the average run length (ARL) when the process is in control and out of control. Evaluating the ARL values for the MEWMA chart through simulation, we determine optimal chart parameters given cost information. Results are presented on model sensitivity (in terms of expected cost and out-of-control ARL) to misspecification of the size of the shift in the process mean vector. We also consider the impact of perturbing the sampling interval on expected cost.

KW - Economic Control Charts

KW - Exponentially Weighted Moving Average Control Charts

KW - Multivariate Control Charts

UR - http://www.scopus.com/inward/record.url?scp=0001264294&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0001264294&partnerID=8YFLogxK

M3 - Article

VL - 32

SP - 410

EP - 417

JO - Journal of Quality Technology

JF - Journal of Quality Technology

SN - 0022-4065

IS - 4

ER -