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Your search keyword '"Dovere, Emanuele"' showing total 24 results
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24 results on '"Dovere, Emanuele"'

2. Using Total Cost of Ownership to Compare Supplier Product-Service System Offering

Author

Pezzotta, Giuditta, Pezzotta, Gianluca, Dovere, Emanuele, Pirola, Fabiana, Gaiardelli, Paolo, Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Liyanage, Jayantha P., editor, Amadi-Echendu, Joe, editor, and Mathew, Joseph, editor

Published
2020
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3. A Dual Perspective Workflow to Improve Data Collection for Maintenance Delivery: An Industrial Case Study

Author

Sala, Roberto, Pirola, Fabiana, Dovere, Emanuele, Cavalieri, Sergio, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Pras, Aiko, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Furbach, Ulrich, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Ameri, Farhad, editor, Stecke, Kathryn E., editor, von Cieminski, Gregor, editor, and Kiritsis, Dimitris, editor

Published
2019
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8. RFId systems for moveable asset management: an assessment model.

Author

Dovere, Emanuele, Cavalieri, Sergio, and Ierace, Stefano

Subjects
ASSET management, MANUFACTURING industries, PRODUCTION planning, MACHINING, PRODUCT life cycle, RADIO frequency
Abstract

Management of moveable assets is a key issue in most industrial manufacturing companies. With the increasing complexity of production systems characterised by numerous and heterogeneous machining centres, it becomes quite hard to carry out an effective and cost-efficient management model of the tools and fixtures needed for ensuring a correct and timely execution of the planned production cycles. A prerequisite for a proper management of moveable assets is the adoption of identification systems to support the traceability and data collection of the most relevant pieces of information along the life cycle of an asset. The aim of this paper was to provide an assessment model for evaluating the benefits and costs related to the adoption of RFId tags as identifications systems for moveable assets, and in particular in managing machinery tools in a production premise. In order to present a practical example of applicability of the model, an industrial application is reported with an in-depth analysis of the potential benefits and issues derived from the implementation of RFId tags. [ABSTRACT FROM AUTHOR]

Published
2017
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9. Il Machine Learning a supporto della diagnostica

Author

Dovere, Emanuele, Sala, Roberto, and Vernieri, Mariangela

Subjects
Machine Learning, Manutenzione, Diagnostica, Industria 4.0, Maintenance, Machien Learning, Settore ING-IND/17 - Impianti Industriali Meccanici, Diagnostic, Industry 4.0
Published
2019

22. Metodologia di applicazione della firma elettrica

Author

Macchi, Marco, Fumagalli, Luca, Garetti, Marco, Dovere, Emanuele, Cavalieri, Sergio, Ierace, Stefano, Cristaldi, Loredana, Rossi, Marco, Zaltieri, R., and Vernieri, M.

Subjects
Settore ING-IND/17 - Impianti Industriali Meccanici
Published
2011

23. An artificial immune intelligent maintenance system for distributed industrial environments

Author

Emmanouilidis, Christos, Iung, Benoit, Macchi, Marco, Peres, Francois, Fasanotti, Luca, Cavalieri, Sergio, Dovere, Emanuele, Gaiardelli, Paolo, and Pereira, Carlos E

Abstract

Maintenance services of geographically dispersed industrial applications, such as oil transfer systems via pipelines and wastewater treatment plants, are affected by high logistics costs and risks of permanent downtimes. The increasing availability of smart technologies and devices has led to the introduction of advanced prognostic and diagnostic systems to support maintenance activities. In this context, artificial immune systems support the development of industrial applications, where machines and equipment are capable of self-repairing, healing and learning due to their ability to learn from experience. However, the applicability of artificial immune systems has a limited set of contexts along with a low incidence of real-word implementations in the literature, and thus, additional explorative studies are necessary. This article describes a proposed hybrid system conceived by integrating a multi-agent system–based architecture with the main features of artificial immune systems and evaluates its potential applications in two different industrial settings. The flexibility of the behaviour of artificial immune systems methodologies allows for the implementation of a reliable diagnostic and prognostic system, while the choice of multi-agent system architecture enables a mix of autonomy and distributed processing that overcomes the strong limitations of a reduced training dataset.

Published
2018
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