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...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
2017
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| Sorozat: | 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 |
| Tartalmi kivonat: | 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. |
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| Terjedelem/Fizikai jellemzők: | 36-40 |
| ISSN: | 2064-7964 |