This Thesis describes an industrial procedure tailored to the company Unox S.p.A. for data analysis through multivariate statistical methodologies. Process variables are analysed for process understanding, data-driven design (creation of intuitive user-machine interface for improved user experience), process monitoring (anomalies detection during cooking process to ensure final product quality) and predictive maintenance (data-based equipment failure prediction for improved after-sale service).
Data analysis through multivariate statistical techniques: an industrial application
Jignea, Doina
2020/2021
Abstract
This Thesis describes an industrial procedure tailored to the company Unox S.p.A. for data analysis through multivariate statistical methodologies. Process variables are analysed for process understanding, data-driven design (creation of intuitive user-machine interface for improved user experience), process monitoring (anomalies detection during cooking process to ensure final product quality) and predictive maintenance (data-based equipment failure prediction for improved after-sale service).File in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/21109