A modified CUSUM control chart for monitoring industrial processes

Muhammad Faisal; Raja Fawad Zafar; Nasir Abbas; Muhammad Riaz; Tahir Mahmood

doi:10.1002/qre.2307

A modified CUSUM control chart for monitoring industrial processes

Muhammad Faisal, Raja Fawad Zafar, Nasir Abbas^*, Muhammad Riaz, Tahir Mahmood

^*Corresponding author for this work

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

Abstract

Control charts are the most popular tool of statistical process control for monitoring variety of processes. The detection ability of these control charts can be improved by introducing various transformations. In this study, we have enhanced the performance of CUSUM charts by introducing a link relative variable transformation technique. Link relative variable converts the original process variable in a form which is relative to its mean. So, the link relative represents the relative positioning of the observations. Average run length (ARL) is used to compare our technique with the previous studies. The comparison shows the overall good detection performance of our scheme for a span of shifts in the mean. A real‐world example from the electrical engineering process is also included to demonstrate the application of proposed control chart.

Original language	English
Pages (from-to)	1045-1058
Number of pages	14
Journal	Quality and Reliability Engineering International
Volume	34
Issue number	6
DOIs	https://doi.org/10.1002/qre.2307
Publication status	Published - Oct 2018
Externally published	Yes

Keywords

average run length
control chart
cumulative sum
link relative
statistical process control

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10.1002/qre.2307

Cite this

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title = "A modified CUSUM control chart for monitoring industrial processes",

abstract = "Control charts are the most popular tool of statistical process control for monitoring variety of processes. The detection ability of these control charts can be improved by introducing various transformations. In this study, we have enhanced the performance of CUSUM charts by introducing a link relative variable transformation technique. Link relative variable converts the original process variable in a form which is relative to its mean. So, the link relative represents the relative positioning of the observations. Average run length (ARL) is used to compare our technique with the previous studies. The comparison shows the overall good detection performance of our scheme for a span of shifts in the mean. A real‐world example from the electrical engineering process is also included to demonstrate the application of proposed control chart.",

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AU - Faisal, Muhammad

AU - Zafar, Raja Fawad

AU - Abbas, Nasir

AU - Riaz, Muhammad

AU - Mahmood, Tahir

PY - 2018/10

Y1 - 2018/10

N2 - Control charts are the most popular tool of statistical process control for monitoring variety of processes. The detection ability of these control charts can be improved by introducing various transformations. In this study, we have enhanced the performance of CUSUM charts by introducing a link relative variable transformation technique. Link relative variable converts the original process variable in a form which is relative to its mean. So, the link relative represents the relative positioning of the observations. Average run length (ARL) is used to compare our technique with the previous studies. The comparison shows the overall good detection performance of our scheme for a span of shifts in the mean. A real‐world example from the electrical engineering process is also included to demonstrate the application of proposed control chart.

AB - Control charts are the most popular tool of statistical process control for monitoring variety of processes. The detection ability of these control charts can be improved by introducing various transformations. In this study, we have enhanced the performance of CUSUM charts by introducing a link relative variable transformation technique. Link relative variable converts the original process variable in a form which is relative to its mean. So, the link relative represents the relative positioning of the observations. Average run length (ARL) is used to compare our technique with the previous studies. The comparison shows the overall good detection performance of our scheme for a span of shifts in the mean. A real‐world example from the electrical engineering process is also included to demonstrate the application of proposed control chart.

KW - average run length

KW - control chart

KW - cumulative sum

KW - link relative

KW - statistical process control

UR - https://scholars.cityu.edu.hk/en/publications/a-modified-cusum-control-chart-for-monitoring-industrial-processes(27d6e22b-8ee3-4f63-8344-9d15db73c68c).html

U2 - 10.1002/qre.2307

DO - 10.1002/qre.2307

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EP - 1058

JO - Quality and Reliability Engineering International

JF - Quality and Reliability Engineering International

IS - 6

ER -

A modified CUSUM control chart for monitoring industrial processes

Abstract

Keywords

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