A Control Chart Based on Sample Median for the Detection of a Permanent Shift in the Process Mean

Khoo, Michael B. C.

doi:10.1081/qen-200057329

Cited by 46 publications

(27 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Exponentially Weighted Moving Average (EWMA) median chart was introduced by Castagliola (exponentially weighted moving average‐

\overset{X}{true}

) with fast detection of assignable causes. Khoo proposed a Shewhart‐

\overset{X}{true}

control chart for practitioners who are only interested in the detection of permanent shifts in the process mean. As a continuation to improve the statistical performance of median type control charts, generally weighted moving average median‐

\overset{X}{true}

control chart has been studied by Sheu and Yang .…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Shewhart median Chart in the Presence of Measurement Errors

Tran

Castagliola

Balakrishnan

2016

Quality & Reliability Eng

View full text Add to dashboard Cite

In the literature, median control charts have been introduced under the assumption of no measurement error. However, measurement errors always exist in practice and may considerably affect the ability of control charts to detect out‐of‐control situations. In this paper, we investigate the performance of Shewhart median chart by using a linear covariate error model. Several figures and tables are presented and commented to show the statistical performance of Shewhart median control chart in the presence of measurement errors. We also investigate the positive effect of taking multiple measurements for each item in a subgroup on the performance of Shewhart median chart. An example illustrates the use of Shewhart median chart in the presence of measurement errors. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

“…Exponentially Weighted Moving Average (EWMA) median chart was introduced by Castagliola (exponentially weighted moving average‐

\overset{X}{true}

) with fast detection of assignable causes. Khoo proposed a Shewhart‐

\overset{X}{true}

\overset{X}{true}

control chart has been studied by Sheu and Yang .…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Shewhart median Chart in the Presence of Measurement Errors

Tran

Castagliola

Balakrishnan

2016

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…, where f is the unknown density of F. The variety of the median control charts comes from a group of various consistent estimates of 1/(4 f 2 (θ)) (Nelson, 1982;Janacek and Meikle, 1997;Khoo, 2005). Park (2008Park ( , 2009 proposed several median control charts through an estimation of the variance ofθ with various bootstrap methods.…”

Section: Median Control Charts Based On the Estimated Limiting Variancementioning

confidence: 99%

A Note on the Median Control Chart

Park¹

2013

Communications for Statistical Applications and Methods

View full text Add to dashboard Cite

This study reviews several well-known control charts for the location parameter with a discussion of the relationship between the maintenance of the control chart and a series of hypotheses testing. As a by-product, we then propose a new median control chart with the sign test statistic. We also modify the nonparametric control charts to easily understand the relation. Then we illustrate the construction of several median control charts with the industrial data and compare the efficiency among several control charts. Finally, we discuss some interesting features for the median control charts as concluding remarks.

show abstract

“…The sample med ian is a robust estimator of location for samples, and it is ease of computation and offers advantages when the population is skewed. Moreover, the med ian chart can maintain the chart's sensitivity in the presence of outliers [3]. Thus, the sample median could be an alternative statistical to monitor TBE data.…”

Section: Introductionmentioning

confidence: 99%

Design of Exponential Distributed Median Chart with Unknown Parameters

Cao¹,

Ma²

2018

Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

View full text Add to dashboard Cite

Abstract-It is recommended to monitor the time between events(TBE) when the defect rate is very low. An unbiased median chart is proposed to monitor exponential distributed TBE data and some design parameters are provided for ease of application. For the parameter is usually unknown, the effects of estimation on the chart performance are evaluated in terms of conditional false alarm rate and the conditional average run length(ARL) distribution. It is find that the median statistical can significantly reduce the "practitioner-to-practitioner" variability, and less number of reference samples are needed in phase I control chart. Moreover, the median chart ensures the sensitivity of the process shift to a certain extent. It is shown that the median statistical is an alternative one to monitor the exponential distributed TBE data.

show abstract

A Control Chart Based on Sample Median for the Detection of a Permanent Shift in the Process Mean

Cited by 46 publications

References 4 publications

On the Performance of Shewhart median Chart in the Presence of Measurement Errors

On the Performance of Shewhart median Chart in the Presence of Measurement Errors

A Note on the Median Control Chart

Design of Exponential Distributed Median Chart with Unknown Parameters

Contact Info

Product

Resources

About