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27 January 2020
Article (Scientific journals)
Monitoring process variation using modified EWMA
Saghir, Aamir; Aslam, Muhammad; Faraz, Alireza  et al.
2020 • In Quality and Reliability Engineering International, 36 (1), p. 328-339
Peer Reviewed verified by ORBi
 

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Keywords :
Monte Carlo simulation; Flowcharting; Graphic methods; Intelligent systems; Monte Carlo methods; Exponentially weighted moving average control charts; Monitoring process; Process variance; Process Variation; Run length; Sample sizes; Smoothing constant; Standard deviation; Control charts
Abstract :
[en] A new control chart, namely, modified exponentially weighted moving average (EWMA) control chart, for monitoring the process variance is introduced in this work by following the recommendations of Khan et al.15 The proposed control chart deduces the existing charts to be its special cases. The necessary coefficients, which are required for the construction of modified EWMA chart, are determined for various choices of sample sizes and smoothing constants. The performance of the proposed modified EWMA is evaluated in terms of its run length (RL) characteristics such as average RL and standard deviation of RL. The efficiency of the modified EWMA chart is investigated and compared with some existing control charts. The comparison reveals the superiority of proposal as compared with other control charts in terms of early detection of shift in process variation. The application of the proposal is also demonstrated using a real-life dataset. © 2019 John Wiley & Sons, Ltd.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Saghir, Aamir;  Department of Mathematics, Mirpur University of Science and Technology (MUST), AJK, Mirpur, 10250, Pakistan
Aslam, Muhammad;  Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, 21551, Saudi Arabia
Faraz, Alireza ;  Université de Liège - ULiège > HEC Liège : UER > UER Opérations: Statistique appl. à la gest. et à l'économie
Ahmad, Liaquat;  Department of Statistics and computer Science, UVAS Business School, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
Heuchenne, Cédric ;  Université de Liège - ULiège > HEC Liège : UER > UER Opérations: Statistique appl. à la gest. et à l'économie
Language :
English
Title :
Monitoring process variation using modified EWMA
Publication date :
2020
Journal title :
Quality and Reliability Engineering International
ISSN :
0748-8017
eISSN :
1099-1638
Publisher :
John Wiley and Sons Ltd
Volume :
36
Issue :
1
Pages :
328-339
Peer reviewed :
Peer Reviewed verified by ORBi

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