Statistical process control for the analysis of quality control in urodynamics: A potential new approach for quality review of urodynamics

Zeng, Xiao; Shen, Sihong; Shen, Hong; Luo, Deyi

doi:10.1002/nau.25081

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…The control chart comprises three lines: the Center Line, also known as CL, which represents the average value of quality attributes; the Upper Control Limit, also known as UCL; and the Lower Control Limit, also known as LCL. The UCL and LCL are the upper and lower control limits, respectively (Zeng et al, 2023). Figure 2 is an example of a control chart for some conditions.…”

Section: B Methodsmentioning

confidence: 99%

Control Chart for Correcting the ARIMA Time Series Model of GDP Growth Cases

Imro'ah,

Huda,

Utami

et al. 2024

JTAM

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The essential prerequisite for attending the G20 conference is a country's GDP because G20 members can significantly boost the economy and preserve the nation's financial stability. Time series data can be thought of as a country's Gross Domestic Product (GDP) at a particular point in time. In this research, the GDP numbers from five Southeast Asian nations that are attending the G20 fulfilling are used. The total was 47 observations made yearly, which extended from 1975 to 2001. A time series analysis was performed on the data gathered. The correctness of time series models is also evaluated using control charts based on this research. The control chart is constructed using the time series model's residuals as observations. After applying the IMR control chart for verification, the results revealed that the residuals, specifically the models for GDP in Malaysia, Singapore, and Thailand, are out of control. The white noise assumption is fulfilled by the time series model obtained for Brunei and Indonesia's GDP, but the residuals are out of control. Whether controlled residuals are used depends on the accuracy with which the time series model predicts the future. If the amount of residuals is under control, then the time series model produced is accurate and good enough for prediction. After using the IMR control chart to verify the residuals, the results indicate that the residuals, namely the models for GDP in Malaysia, Singapore, and Thailand, are not under control. The assumption of white noise is proved correct by the time series model obtained for the GDP of Brunei Darussalam and Indonesia. With that being said, the residuals are entirely out of control. The model must improve its ability to forecast various future periods. It is a consequence of the unmanageable residuals that the model contains. Even if the best available model has been obtained based on the criteria that have been defined, it is anticipated that the research findings will improve the theories that have previously been developed and raise knowledge regarding the usefulness of testing the time series model. In addition to all of that, it is intended that the research will produce a summary of cases of an increase in GDP from five Southeast Asian countries participating in the G20 conference.

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Section: B Methodsmentioning

confidence: 99%