A new scheme of dispersion charts based on neoteric ranked set sampling

Abstract

There are certain areas of science and technology, such as agriculture, ecology, and environmental studies, that emphasize designing competent sampling strategies. The ranked set schemes, particularly the neoteric ranked set sampling (NRSS), are one method that meets such objectives. The NRSS provides plans that incorporates expert knowledge while choosing samples, which is beneficial. This study proposes a novel scheme for creating dispersion charts based on NRSS. The proposed scheme aims to improve the accuracy of dispersion charts by reducing the impact of outliers and non-normality in data sets. As a highly effective method in estimating population parameters, NRSS is used to select samples from the data set. The proposed dispersion charts are assessed based on individual performance measure criteria at shifts of different magnitudes. The dispersion charts created using this new scheme are compared with traditional dispersion charts, and the results demonstrate that the proposed scheme produces charts with higher accuracy and robustness. The study highlights the potential benefits of using NRSS-based dispersion charts in various fields, including quality control, environmental monitoring, and process control. An actual data application from a non-isothermal continuous stirred tank chemical reactor model further validates the simulation results.

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