Efficient monitoring of coefficient of variation with an application to chemical reactor process

Abstract

Control chart is a useful tool to monitor the performance of the industrial or production processes. Control charts are mostly adopted to detect unfavorable variations in process location (mean) and dispersion (standard deviation) parameters. In the literature, many control charts are designed for the monitoring of process variability under the assumption that the process mean is constant over time and the standard deviation is independent of the mean. However, for many real‐life processes, the standard deviation may be proportional to mean, and hence it is more appropriate to monitor the process coefficient of variation (CV). In this study, we are proposing a design structure of the Shewhart type CV control chart under neoteric ranked set sampling with an aim to improve the detection ability of the usual CV chart. A comprehensive simulation study is conducted to evaluate the performance of the proposed CV[NRSS] chart in terms of ARL, MDRL, and SDRL measures. Moreover, the comparison of CV[NRSS] chart is made with the existing competitive charts, based on simple random sampling, ranked set sampling (RSS), median RSS, and extreme RSS schemes. The results revealed that the proposed chart has better detection ability as compared to all existing competitive charts. Finally, a real‐life example is presented to illustrate the working of the newly proposed CV chart.

A variable sample size run sum coefficient of variation chart

“…Monitoring γ is also important in medical diagnostics to monitor the amount of chemicals that varies according to the daily activities of the patient. Several recent studies on monitoring γ can be found in the literature 11–17 …”

Monitoring multivariate coefficient of variation with individual observations

“…Additionally, Lee et al 21 presented a study on the effect of measurement errors on the performance of a two-sided SH CV chart in short production runs. Mahmood and Abbasi 22 proposed an efficient monitoring of the CV with an application to the chemical reactor process, where the Shewhart CV chart under neoteric ranked-set sampling, based on extensive simulation study was considered in evaluating the chart's performance. In the same vein, Saha et al 23 developed the side-sensitive modified group runs charts with and without measurement errors for monitoring the CV.…”

On the location‐based memory type control charts under modified successive sampling scheme

“…For monitoring process variability, Munir and Haq 19 proposed CUSUM control charts based on ordered RSS and double ordered RSS. The linear profiles monitoring based on RSS and its improvements can be found in 20–24 . Nawaz et al 25 .…”

“…The linear profiles monitoring based on RSS and its improvements can be found in. [20][21][22][23][24] Nawaz et al 25 and Nawaz and Han 26 evaluated the Shewhart, CUSUM, EWMA, and HWMA charts for a normal process to detect shifts in the mean by using the neoteric RSS scheme. Hussain et al 27 compared different median based Shewhart, CUSUM, and EWMA control charts for location monitoring using RSS and neoteric RSS sampling schemes.…”