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Zambonin, Giuliano (2019) Development of Machine Learning-based technologies for major appliances: soft sensing for drying technology applications. [Ph.D. thesis]

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Abstract (italian or english)

In this thesis, Machine Learning techniques for the improvements in the performance of household major appliances are described. In particular, the focus is on drying technologies and domestic dryers are the machines of interest selected as case studies. Statistical models called Soft Sensors have been developed to provide estimates of quantities that are costly/time-consuming to measure in our applications using data that were available for other purposes.
The work has been developed as industrially driven research activity in collaborations with Electrolux Italia S.p.a. R&D department located in Porcia, Pordenone, Italy. During the thesis, practical aspects of the implementation of the proposed approaches in a real industrial environment as well as topics related to collaborations between industry and academies are specified.


EPrint type:Ph.D. thesis
Tutor:Susto , Gian Antonio
Supervisor:Beghi, Alessandro
Ph.D. course:Ciclo 32 > Corsi 32 > INGEGNERIA DELL'INFORMAZIONE > SCIENZA E TECNOLOGIA DELL'INFORMAZIONE
Data di deposito della tesi:27 December 2019
Anno di Pubblicazione:27 December 2019
Key Words:soft sensing, drying technology, fabric care, sparse regularization, symbolic regression, functional linear models, multiple linear regression,
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 Automatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:12799
Depositato il:25 Jan 2021 13:28
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