LAPSE:2021.0111
Published Article
LAPSE:2021.0111
Multivariate Six Sigma: A Case Study in Industry 4.0
March 14, 2021
The complex data characteristics collected in Industry 4.0 cannot be efficiently handled by classical Six Sigma statistical toolkit based mainly in least squares techniques. This may refrain people from using Six Sigma in these contexts. The incorporation of latent variables-based multivariate statistical techniques such as principal component analysis and partial least squares into the Six Sigma statistical toolkit can help to overcome this problem yielding the Multivariate Six Sigma: a powerful process improvement methodology for Industry 4.0. A multivariate Six Sigma case study based on the batch production of one of the star products at a chemical plant is presented.
Record ID
Keywords
Industry 4.0, latent variables models, multivariate data analysis, PCA, PLS, Six Sigma
Subject
Suggested Citation
Palací-López D, Borràs-Ferrís J, da Silva de Oliveria LT, Ferrer A. Multivariate Six Sigma: A Case Study in Industry 4.0. (2021). LAPSE:2021.0111
Author Affiliations
Palací-López D: International Flavors & Fragrances Inc., IFF (Benicarló), 12580 Benicarló, Spain
Borràs-Ferrís J: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
da Silva de Oliveria LT: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
Ferrer A: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
Borràs-Ferrís J: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
da Silva de Oliveria LT: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
Ferrer A: Multivariate Statistical Engineering Group, Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
Journal Name
Processes
Volume
8
Issue
9
Article Number
E1119
Year
2020
Publication Date
2020-09-09
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr8091119, Publication Type: Journal Article
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Published Article
LAPSE:2021.0111
This Record
External Link
doi:10.3390/pr8091119
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Version History
[v1] (Original Submission)
Mar 14, 2021
Verified by curator on
Mar 14, 2021
This Version Number
v1
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URL Here
https://psecommunity.org/LAPSE:2021.0111
Original Submitter
Calvin Tsay
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