An EWMA control chart for the multivariate ...
Document type :
Article dans une revue scientifique: Article original
DOI :
Permalink :
Title :
An EWMA control chart for the multivariate coefficient of variation
Author(s) :
Giner-Bosch, Vicent [Auteur]
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
Tran, Kim-Phuc [Auteur]
Ecole nationale supérieure des arts et industries textiles de Roubaix (ENSAIT)
Castagliola, Philippe [Auteur]
Laboratoire des Sciences du Numérique de Nantes [LS2N]
Systèmes Logistiques et de Production [LS2N - équipe SLP ]
Khoo, Michael Boon Chong [Auteur]
Universiti Sains Malaysia [USM]
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
Tran, Kim-Phuc [Auteur]
Ecole nationale supérieure des arts et industries textiles de Roubaix (ENSAIT)
Castagliola, Philippe [Auteur]
Laboratoire des Sciences du Numérique de Nantes [LS2N]
Systèmes Logistiques et de Production [LS2N - équipe SLP ]
Khoo, Michael Boon Chong [Auteur]
Universiti Sains Malaysia [USM]
Journal title :
Quality and Reliability Engineering International
Abbreviated title :
Qual. Reliab. Eng. Int.
Volume number :
35
Pages :
1515-1541
Publication date :
2019-10-05
ISSN :
0748-8017
English keyword(s) :
average run length
doubly noncentral F distribution
EWMA
multivariate coefficient of variation
Nelder-Mead method
trimmed mean
doubly noncentral F distribution
EWMA
multivariate coefficient of variation
Nelder-Mead method
trimmed mean
HAL domain(s) :
Sciences de l'ingénieur [physics]
English abstract : [en]
Monitoring the multivariate coefficient of variation over time is a natural choice
when the focus is on stabilising the relative variability of a multivariate process,
as is the case in a significant number of real ...
Show more >Monitoring the multivariate coefficient of variation over time is a natural choice when the focus is on stabilising the relative variability of a multivariate process, as is the case in a significant number of real situations in engineering, health sciences and finance, to name but a few areas. However, not many tools are available to practitioners with this aim. This paper introduces a new control chart to monitor the multivariate coefficient of variation through an EWMA scheme. Concrete methodologies to calculate the limits and evaluate the performance of the chart proposed, and determine the optimal values of the chart’s parameters are derived, based on a theoretical study of the statistic being monitored. Computational experiments reveal that our proposal clearly outperforms existing alternatives, in terms of the average run length to detect an out-of-control state. A numerical example is included to show the efficiency of our chart when operating in practice.Show less >
Show more >Monitoring the multivariate coefficient of variation over time is a natural choice when the focus is on stabilising the relative variability of a multivariate process, as is the case in a significant number of real situations in engineering, health sciences and finance, to name but a few areas. However, not many tools are available to practitioners with this aim. This paper introduces a new control chart to monitor the multivariate coefficient of variation through an EWMA scheme. Concrete methodologies to calculate the limits and evaluate the performance of the chart proposed, and determine the optimal values of the chart’s parameters are derived, based on a theoretical study of the statistic being monitored. Computational experiments reveal that our proposal clearly outperforms existing alternatives, in terms of the average run length to detect an out-of-control state. A numerical example is included to show the efficiency of our chart when operating in practice.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Submission date :
2023-06-20T11:15:43Z
2024-02-23T09:04:03Z
2024-02-23T09:04:03Z