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Multivariate Statistical Quality Control Using R

Part of the SpringerBriefs in Statistics Book Series (volume 14)

DOI: 10.1007/978-1-4614-5453-3

ISBN: 978-1-4614-5452-6

Publisher: Springer New York - Springer Journals

Aug 23, 2012

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A Small Introduction

Santos-Fernández, Edgar

Pages: 1 –15

[The first chapter provides a very short introduction about R language, statistical procedures, and the main aspects concerning Statistical Quality Control (SQC). It is recommended for beginners.]
Available

Multivariate Control Charts

Santos-Fernández, Edgar

Pages: 17 –61

[This chapter is devoted to the main aspects concerning the multivariate control charts. It covers the multivariate normal distribution, the data structure, and the mult.chart function that allows the computation in R and the most used multivariate control charts such as the χ2, T2, the...
Available

Multivariate Process Capability Indices (MPCI)

Santos-Fernández, Edgar

Pages: 63 –85

[In this chapter the most recognized multivariate process capability indices are presented. The first section approaches the computation of these indices in R, and the next ones are dedicated to the indices based on ratios of the volume tolerance region to a process region such as Taam et al. (J...
Available

Tools of Support to MSQC

Santos-Fernández, Edgar

Pages: 87 –106

[As a general rule, normality and independence of the data is required in Statistical Process Control and the multivariate extensions are not the exception. Different tools are presented—graphical methods, marginal and multivariate normality test, solutions to the departures from normality, and a...
Available

Study Cases

Santos-Fernández, Edgar

Pages: 107 –119

[This chapter deals with the application of the techniques introduced to the baseball pitcher performance and to the target archery, and it links the use of control charts and capability measures with the assessing of normality and independence. It provides practitioners a step-by-step practical...

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