The efficiency of run rules schemes for multivariate coefficient of variation: A Markov chain approach

Chew, X. Y. and Khaw, K. W. and Yeong, W. C. * (2020) The efficiency of run rules schemes for multivariate coefficient of variation: A Markov chain approach. Journal of Applied Statistics, 47 (3). pp. 460-480. ISSN 1360-0532

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Control charts are one of the important tools to monitor quality. The coefficient of variation (CV) is a common measure of dispersion in many real-life applications. Recently, CV control charts are proposed to monitor processes which do not have a constant mean and a standard deviation which changes with the mean. These processes cannot be monitored by standard control charts which monitor the mean and/or standard deviation. This research proposes the monitoring of the multivariate coefficient of variation (MCV) by means of run rules (RR MCV) control charts, which is not available in the existing literature. The design of these charts is obtained using a Markov-chain approach. The proposed charts are simple to implement. The performance of the RR MCV and Shewhart MCV (SH MCV) charts are compared in terms of the average run length (ARL) and the expected average run length (EARL). An example is illustrated based on a real dataset. The findings revealed that the performance of the proposed charts surpasses the SH MCV chart for detecting small and moderate MCV shifts.

Item Type: Article
Uncontrolled Keywords: Average run length; expected average run length; markov-chain; multivariate coefficient of variation; run rules
Subjects: Q Science > QA Mathematics
Divisions: Others > Non Sunway Academics
Sunway University > School of Mathematical Sciences > Department of Applied Statistics
Depositing User: Dr Janaki Sinnasamy
Date Deposited: 02 Oct 2020 05:49
Last Modified: 02 Oct 2020 05:49

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