View in EDS PDF Full Text

Design and Application of Mixed Tukey DMA-EWMA Control Charts for Enhanced Process Mean Monitoring.

Saved in:
Bibliographic Details
Title: Design and Application of Mixed Tukey DMA-EWMA Control Charts for Enhanced Process Mean Monitoring.
Authors: Taboran, Rattikarn1 rattikarntab@mcru.ac.th, Areepong, Yupaporn2 yupaporn.a@sci.kmutnb.ac.th, Sukparungsee, Saowanit2 saowanit.s@sci.kmutnb.ac.th
Source: Engineering Letters. May2026, Vol. 34 Issue 5, p1772-1783. 12p.
Subjects: Statistical process control, Quality control charts, Process control systems, Monte Carlo method
Abstract: Nonparametric control charts are a type of statistical tool for process monitoring with no need to rely on assumptions about data distributions. Undoubtedly, they are flexible and more suitable in reality. The objectives of this research are to propose a new nonparametric control chart, the Tukey double moving average - exponentially weighted moving average (Tukey DMA-EWMA), and to compare shift detection efficiency and the other control charts, namely Tukey EWMA-DMA, DMA-EWMA, EWMA-DMA, TCC, DMA, and EWMA. This study used Monte Carlo Simulation (MC) to assess efficiency of these control charts under various distributions: normal, Laplace, gamma, and Weibull. Sizes of shifts were set between -3.00 to 3.00. As for the measurement criteria of average run length (ARL) and median run length (MRL). The results revealed as follows: 1) Under normal distribution and Laplace distribution at the shift levels of ±1.00, ±1.50, ±2.00, ±2.50, and ±3.00, Tukey DMA-EWMA had better detection efficiency than the other control charts, 2) Under gamma distribution, Tukey DMA-EWMA had the highest detection efficiency on the shifted averages of the process at all shift levels and 3) Applying the subject control chart to real industrial data conformed to the results of the simulations. This indicated the suitability of the proposed control chart. This implied that Tukey DMA-EWMA is an efficient option for process monitoring when data is not in accordance with normal distribution or when flexibility is required for real use. [ABSTRACT FROM AUTHOR]
Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 193453933
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Design and Application of Mixed Tukey DMA-EWMA Control Charts for Enhanced Process Mean Monitoring.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Taboran%2C+Rattikarn%22">Taboran, Rattikarn</searchLink><relatesTo>1</relatesTo><i> rattikarntab@mcru.ac.th</i><br /><searchLink fieldCode="AR" term="%22Areepong%2C+Yupaporn%22">Areepong, Yupaporn</searchLink><relatesTo>2</relatesTo><i> yupaporn.a@sci.kmutnb.ac.th</i><br /><searchLink fieldCode="AR" term="%22Sukparungsee%2C+Saowanit%22">Sukparungsee, Saowanit</searchLink><relatesTo>2</relatesTo><i> saowanit.s@sci.kmutnb.ac.th</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Engineering+Letters%22">Engineering Letters</searchLink>. May2026, Vol. 34 Issue 5, p1772-1783. 12p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Statistical+process+control%22">Statistical process control</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+control+charts%22">Quality control charts</searchLink><br /><searchLink fieldCode="DE" term="%22Process+control+systems%22">Process control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Nonparametric control charts are a type of statistical tool for process monitoring with no need to rely on assumptions about data distributions. Undoubtedly, they are flexible and more suitable in reality. The objectives of this research are to propose a new nonparametric control chart, the Tukey double moving average - exponentially weighted moving average (Tukey DMA-EWMA), and to compare shift detection efficiency and the other control charts, namely Tukey EWMA-DMA, DMA-EWMA, EWMA-DMA, TCC, DMA, and EWMA. This study used Monte Carlo Simulation (MC) to assess efficiency of these control charts under various distributions: normal, Laplace, gamma, and Weibull. Sizes of shifts were set between -3.00 to 3.00. As for the measurement criteria of average run length (ARL) and median run length (MRL). The results revealed as follows: 1) Under normal distribution and Laplace distribution at the shift levels of ±1.00, ±1.50, ±2.00, ±2.50, and ±3.00, Tukey DMA-EWMA had better detection efficiency than the other control charts, 2) Under gamma distribution, Tukey DMA-EWMA had the highest detection efficiency on the shifted averages of the process at all shift levels and 3) Applying the subject control chart to real industrial data conformed to the results of the simulations. This indicated the suitability of the proposed control chart. This implied that Tukey DMA-EWMA is an efficient option for process monitoring when data is not in accordance with normal distribution or when flexibility is required for real use. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193453933
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 1772
    Subjects:
      – SubjectFull: Statistical process control
        Type: general
      – SubjectFull: Quality control charts
        Type: general
      – SubjectFull: Process control systems
        Type: general
      – SubjectFull: Monte Carlo method
        Type: general
    Titles:
      – TitleFull: Design and Application of Mixed Tukey DMA-EWMA Control Charts for Enhanced Process Mean Monitoring.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Taboran, Rattikarn
      – PersonEntity:
          Name:
            NameFull: Areepong, Yupaporn
      – PersonEntity:
          Name:
            NameFull: Sukparungsee, Saowanit
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1816093X
          Numbering:
            – Type: volume
              Value: 34
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Engineering Letters
              Type: main
ResultId 1