A new hwma dispersion control chart with an application to wind farm data

Muhammad Riaz; Saddam Akber Abbasi; Abdulhammed K. Hamzat; Muhammad Abid

doi:10.3390/math8122136

A new hwma dispersion control chart with an application to wind farm data

Muhammad Riaz^*
, Saddam Akber Abbasi
, Abdulhammed K. Hamzat
, Muhammad Abid

^*Corresponding author for this work

Department of Mathematics

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

20 Scopus citations

Abstract

Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart’s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.

Original language	English
Article number	2136
Pages (from-to)	1-14
Number of pages	14
Journal	Mathematics
Volume	8
Issue number	12
DOIs	https://doi.org/10.3390/math8122136
State	Published - Dec 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

Average run length
EWMA
HWMA
Processes dispersion
Small shifts

ASJC Scopus subject areas

Computer Science (miscellaneous)
General Mathematics
Engineering (miscellaneous)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/math8122136

Cite this

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title = "A new hwma dispersion control chart with an application to wind farm data",

abstract = "Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart{\textquoteright}s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.",

keywords = "Average run length, EWMA, HWMA, Processes dispersion, Small shifts",

author = "Muhammad Riaz and Abbasi, \{Saddam Akber\} and Hamzat, \{Abdulhammed K.\} and Muhammad Abid",

note = "Publisher Copyright: {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2020",

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doi = "10.3390/math8122136",

language = "English",

volume = "8",

pages = "1--14",

journal = "Mathematics",

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AU - Riaz, Muhammad

AU - Abbasi, Saddam Akber

AU - Hamzat, Abdulhammed K.

AU - Abid, Muhammad

PY - 2020/12

Y1 - 2020/12

N2 - Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart’s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.

AB - Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart’s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.

KW - Average run length

KW - EWMA

KW - HWMA

KW - Processes dispersion

KW - Small shifts

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DO - 10.3390/math8122136

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EP - 14

JO - Mathematics

JF - Mathematics

IS - 12

M1 - 2136

ER -

A new hwma dispersion control chart with an application to wind farm data

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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