Exponentially weighted moving average control charts for monitoring coefficient of variation under ranked set-sampling schemes

Abstract

Several coefficients of variation (CV) control charts under simple random schemes (SRS) have been proposed to monitor process relative variability. However, little attention has been given to investigating the performance of the CV charts under ranked sampling schemes. This study investigates the performance of two one-sided exponentially weighted moving average (EWMA) based CV charts for monitoring downward and upward shifts in the relative variability parameter under ranked set-sampling schemes. The charts are constructed under different sampling schemes, including ranked set-sampling (RSS), median RSS (MRSS), extreme RSS (ERSS), systematic RSS (SRSS), and neoteric RSS (NRSS). Simulation results are presented to show the run length performance of the charts. The results indicate that the downward and upward EWMA-CV charts based on the ranked set sampling outperform the charts constructed under SRS. An illustrative example is provided to show the application of the charts.

KEYWORDS:

• Average run length
• control chart
• Coefficient of variation (CV)
• EWMA
• ranked sampling schemes

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Open Access funding provided by the Qatar National Library.