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Article Dans Une Revue Journal of Statistical Computation and Simulation Année : 2019

One-Sided Synthetic control charts for monitoring the Multivariate Coefficient of Variation

Résumé

Shewhart's type control charts for monitoring the Multivariate Coefficient of Variation (MCV) have recently been proposed in order to monitor the relative variability compared with the mean. These approaches are known to be rather slow in the detection of small or moderate process shifts. In this paper, in order to improve the detection efficiency, two one-sided Synthetic charts for the MCV are proposed. A Markov chain method is used to evaluate the statistical performance of the proposed charts. Furthermore, computational experiments reveal that the proposed control charts outperform the Shewhart MCV control chart in terms of the average run length to detect an out-of-control state. Finally, the implementation of the proposed chart is illustrated with an example using steel sleeves data.
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Dates et versions

hal-01885435 , version 1 (01-10-2018)
hal-01885435 , version 2 (01-04-2019)

Identifiants

Citer

Thong Nguyen, Kim Phuc Tran, P. Castagliola, Giovanni Celano, Salim Lardjane. One-Sided Synthetic control charts for monitoring the Multivariate Coefficient of Variation. Journal of Statistical Computation and Simulation, In press, ⟨10.1080/00949655.2019.1600694⟩. ⟨hal-01885435v1⟩
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