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Distribution-Free Methods for Statistical Process Monitoring and Control [electronic resource] / edited by Markos V. Koutras, Ioannis S. Triantafyllou.

Contributor(s): Koutras, Markos V [editor.] | Triantafyllou, Ioannis S [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: IX, 257 p. 53 illus., 17 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030250812.Subject(s): Industrial Management | Statistics  | Information technology—Management | Industrial Management | Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Business Process ManagementAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 658.5 Online resources: Click here to access online
Contents:
An Overview of Nonparametric Control Charts -- Distribution-free Control Charts for Monitoring the Location Parameter -- Nonparametric Control Charts for Monitoring the Dispersion Parameter -- Bivariate Nonparametric Control Charts -- Exponentially Weighted Moving Average Control Charts based on Ranks -- Cumulative Sum Control Charts based on Ranks -- Nonparametric Control Charts based on Order Statistics -- The Run-Length Distribution of Nonparametric Control Charts -- Distribution-free Control Charts for Joint Monitoring Location and Scale -- Distribution-free Phase II Control Charts for Monitoring Continuous Process.
In: Springer Nature eBookSummary: This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.
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An Overview of Nonparametric Control Charts -- Distribution-free Control Charts for Monitoring the Location Parameter -- Nonparametric Control Charts for Monitoring the Dispersion Parameter -- Bivariate Nonparametric Control Charts -- Exponentially Weighted Moving Average Control Charts based on Ranks -- Cumulative Sum Control Charts based on Ranks -- Nonparametric Control Charts based on Order Statistics -- The Run-Length Distribution of Nonparametric Control Charts -- Distribution-free Control Charts for Joint Monitoring Location and Scale -- Distribution-free Phase II Control Charts for Monitoring Continuous Process.

This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.

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