Article (Scientific journals)
Economic statistical design of a multivariate control chart under a Burr XII shock model with multiple assignable causes
Saadatmelli, A.; Seif, A.; Moghadam, M. B. et al.
2018In Journal of Statistical Computation and Simulation, 88 (11), p. 2111-2136
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Keywords :
Burr XII distribution; Economic statistical design
Abstract :
[en] Control charts show the distinction between the random and assignable causes of variation in a process. The real process may be affected by many characteristics and several assignable causes. Therefore, the economic statistical design of multiple control chart under Burr XII shock model with multiple assignable causes can be an appropriate candidate model. In this paper, we develop a cost model based on the optimization of the average cost per unit of time. Indeed, the cost model under the influence of a single match case assignable cause and multiple assignable causes under a same cost and time parameters were compared. Besides, a sensitivity analysis was also presented in which the changeability of loss-cost and design parameters were evaluated based on the changes in cost, time and Burr XII distribution parameters. © 2018 Informa UK Limited, trading as Taylor & Francis Group.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Saadatmelli, A.;  Department of Statistics, Allameh Tabataba’i University, Tehran, Iran
Seif, A.;  Department of Statistics, Bu-Ali Sina University, Hamedan, Iran
Moghadam, M. B.;  Department of Statistics, Allameh Tabataba’i University, Tehran, Iran
Faraz, Alireza ;  Université de Liège - ULg
Language :
English
Title :
Economic statistical design of a multivariate control chart under a Burr XII shock model with multiple assignable causes
Publication date :
2018
Journal title :
Journal of Statistical Computation and Simulation
ISSN :
0094-9655
eISSN :
1563-5163
Publisher :
Taylor & Francis, United Kingdom
Volume :
88
Issue :
11
Pages :
2111-2136
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 15 May 2021

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