• English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • français 
    • English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • Ouvrir une session
Voir le document 
  •   Accueil de DSpace
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • Voir le document
  •   Accueil de DSpace
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • Voir le document
JavaScript is disabled for your browser. Some features of this site may not work without it.
Tout DSpace
  • Communautés & Collections
  • Par date de publication
  • Auteurs
  • Titres
  • Sujets

Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters

Thumbnail
Auteur
Yeganeh A., Shadman A.R., Triantafyllou I.S., Shongwe S.C., Abbasi S.A.
Date
2021
Language
en
DOI
10.1109/ACCESS.2021.3061990
Sujet
Flowcharting
Quality control
Average run lengths
Efficient monitoring
Exponentially weighted moving average
Independent variables
Linear profiles
Manufacturing industries
Profile parameters
Quality characteristic
Control charts
Institute of Electrical and Electronics Engineers Inc.
Afficher la notice complète
Résumé
In usual quality control methods, the quality of a process or product is evaluated by monitoring one or more quality characteristics using their corresponding distributions. However, when the quality characteristic is defined through the relationship between one or more response and independent variables, the regime is referred to as profiles monitoring. In this article, we improve the performance of the Exponentially Weighted Moving Average Range (EWMAR) control charts, which are implemented for monitoring linear profiles (i.e., intercept, slope and average residual between sample and reference lines) by integrating them with run rules in order to quickly detect various magnitudes of shifts in profile parameters. The validation of the proposed control chart is accomplished by examining its performance using the average run length (ARL) criteria. The proposed EWMAR chart with run rules exhibits a much better performance in detecting small and decreasing shifts than the other competing charts. Finally, an example from multivariate manufacturing industry is employed to illustrate the superiority of the EWMAR chart with run rules. © 2013 IEEE.
URI
http://hdl.handle.net/11615/80880
Collections
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]
htmlmap 

 

Parcourir

Tout DSpaceCommunautés & CollectionsPar date de publicationAuteursTitresSujetsCette collectionPar date de publicationAuteursTitresSujets

Mon compte

Ouvrir une sessionS'inscrire
Help Contact
DepositionAboutHelpContactez-nous
Choose LanguageTout DSpace
EnglishΕλληνικά
htmlmap