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An enhanced nonparametric EWMA sign control chart using sequential mechanism


Autoři: Muhammad Riaz aff001;  Muhammad Abid aff002;  Hafiz Zafar Nazir aff003;  Saddam Akber Abbasi aff004
Působiště autorů: Department of Mathematics and Statistics, King Fahad University of Petroleum and Minerals, Dhahran, Saudi Arabia aff001;  Department of Statistics Government College University Faisalabad, Pakistan aff002;  Department of Statistics University of Sargodha, Sargodha, Pakistan aff003;  Department of Mathematics, Statistics and Physics, Qatar University, Doha, Qatar aff004
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225330

Souhrn

Control charts play a significant role to monitor the performance of a process. Nonparametric control charts are helpful when the probability model of the process output is not known. In such cases, the sampling mechanism becomes very important for picking a suitable sample for process monitoring. This study proposes a nonparametric arcsine exponentially weighted moving average sign chart by using an efficient scheme, namely, sequential sampling scheme. The proposal intends to enhance the detection ability of the arcsine exponentially weighted moving average sign chart, particularly for the detection of small shifts. The performance of the proposal is assessed, and compared with its counterparts, by using some popular run length properties including average, median and standard deviation run lengths. The proposed chart shows efficient shift detection ability as compared to the other charts, considered in this study. A real-life application based on the smartphone accelerometer data-set, for the implementation of the proposed scheme, is also presented.

Klíčová slova:

Accelerometers – Cell phones – Charts – Normal distribution – Quality control – Seismic signal processing – Statistical distributions


Zdroje

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2019 Číslo 11
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