One-sided synthetic control charts for monitoring the multivariate coefficient of variation. Issue 10 (3rd July 2019)

• Record Type: Journal Article
• Authors: Nguyen, Quoc Thong; Tran, Kim Phuc; Castagliola, Philippe; Celano, Giovanni; Lardjane, Salim
• Is Part Of: Journal of statistical computation and simulation. Volume 89:Issue 10(2019)
• Page Start: 1841
• Page End: 1862
• Publication Date: 2019-07-03
• Subjects: Synthetic chart -- Markov chain -- multivariate coefficient of variation -- steady-state; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2019.1600694
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: 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.