Investigation of multivariate statistical process control in R environment

At the first stage of our work, the theoretical knowledge needed to use the multivariate statistical process control (MSPC) was explored. Last year, we clarified the sometimes confused concepts, equations, and formulas [1]. At the second stage, R project simulation studies and some food industrial p...

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Bibliographic Details
Main Authors: Mihalkó József
Rajkó Róbert
Format: Article
Published: 2017
Series:Review of faculty of engineering : analecta technica Szegedinensia 11 No. 2
Kulcsszavak:Folyamatszabályozás - többváltozós, Többváltozós függvény - biometria
Online Access:http://acta.bibl.u-szeged.hu/54829
Description
Summary:At the first stage of our work, the theoretical knowledge needed to use the multivariate statistical process control (MSPC) was explored. Last year, we clarified the sometimes confused concepts, equations, and formulas [1]. At the second stage, R project simulation studies and some food industrial practical model investigations are carried out for confirming the MSPC advantages compared with the univariate ones. Furthermore, we analyse, using principal component analysis (PCA), what could cause the outlying values. Moreover, we will demonstrate how to use the MYTdecomposition.
Physical Description:36-40
ISSN:2064-7964