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Multivariate Statistical Quality Control Using R [electronic resource] / by Edgar Santos-Fernández.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Statistics ; 14Publisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: X, 127 p. 55 illus., 28 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781461454533
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 519.5 23
LOC classification:
  • QA276-280
Online resources:
Contents:
An introduction to R -- Basic Statistical and SQC Procedures -- Multivariate Control Charts -- Multivariate Process Capability -- Multivariate tools of support for MSQC -- Appendix -- Index -- Problem -- Solutions.
In: Springer eBooksSummary: The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis.  These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two  parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices. .
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An introduction to R -- Basic Statistical and SQC Procedures -- Multivariate Control Charts -- Multivariate Process Capability -- Multivariate tools of support for MSQC -- Appendix -- Index -- Problem -- Solutions.

The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis.  These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two  parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices. .

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