Optimal design and evaluation of adaptive ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Optimal design and evaluation of adaptive EWMA monitoring schemes for Inverse Maxwell distribution
Author(s) :
Saghir, A. [Auteur]
Hu, X. L. [Auteur]
Tran, Kim-Phuc [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Song, Z. [Auteur]
Hu, X. L. [Auteur]
Tran, Kim-Phuc [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Song, Z. [Auteur]
Journal title :
Computers & Industrial Engineering
Abbreviated title :
Comput. Ind. Eng.
Volume number :
181
Pages :
-
Publication date :
2024-06-29
ISSN :
0360-8352
English keyword(s) :
Monitoring schemes
Inverse Maxwell distribution
AEWMA
Markov chain
ARL
Inverse Maxwell distribution
AEWMA
Markov chain
ARL
HAL domain(s) :
Sciences de l'ingénieur [physics]
English abstract : [en]
Monitoring schemes have been successfully implemented when the underlying data follows a non-normal distribution like the Inverse Maxwell (IM) distribution. The article proposes a new adaptive exponentially weighted moving ...
Show more >Monitoring schemes have been successfully implemented when the underlying data follows a non-normal distribution like the Inverse Maxwell (IM) distribution. The article proposes a new adaptive exponentially weighted moving average (AEWMA) scheme, namely the AIMEWMA, to monitor the IM distributed process. The design parameters of the AIMEWMA scheme are determined via a Markov chain model and its performance is analyzed by its run length (RL) characteristics. The overall model ability is examined using some popular performance tools. The results show that, for most of shifts, the AIMEWMA scheme is more efficient than other available competitors. Moreover, some guidelines regarding the selection of the most effective scheme in practice have been discussed. The applicability of the new scheme is also presented on a real data set.Show less >
Show more >Monitoring schemes have been successfully implemented when the underlying data follows a non-normal distribution like the Inverse Maxwell (IM) distribution. The article proposes a new adaptive exponentially weighted moving average (AEWMA) scheme, namely the AIMEWMA, to monitor the IM distributed process. The design parameters of the AIMEWMA scheme are determined via a Markov chain model and its performance is analyzed by its run length (RL) characteristics. The overall model ability is examined using some popular performance tools. The results show that, for most of shifts, the AIMEWMA scheme is more efficient than other available competitors. Moreover, some guidelines regarding the selection of the most effective scheme in practice have been discussed. The applicability of the new scheme is also presented on a real data set.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Submission date :
2024-07-16T21:21:37Z
2024-09-24T14:03:42Z
2024-09-24T14:03:42Z