IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency: Intelligent Methods for the Factory of the Future: 8 - Brossura

Libro 6 di 9: Technologien für die intelligente Automation
 
9783662578049: IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency: Intelligent Methods for the Factory of the Future: 8
Brossura
ISBN 10: 3662578042 ISBN 13: 9783662578049
Casa editrice: Springer Vieweg, 2018

Sinossi

This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.

Dr. Peter Schüller is postdoctoral researcher at Technische Universität Wien. His research interests are hybrid reasoning systems that combine Knowledge Representation and Machine Learning and applications in the fields of Cyber-Physical systems and Natural Language Processing.




Dalla quarta di copertina

This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction.


The Editors

Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.


Dr. Peter Schüller is postdoctoral researcher at Technische Universität Wien. His research interests are hybrid reasoning systems that combine Knowledge Representation and Machine Learning and applications in the fields of Cyber-Physical systems and Natural Language Processing.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Vieweg
Data di pubblicazione
2018
Lingua
Inglese
ISBN 10 
3662578042
ISBN 13 
9783662578049
Rilegatura
Copertina flessibile
Numero edizione
1
Numero di pagine
140
Redattore
Niggemann Oliver, Schüller Peter
Contatto del produttore
ProductSafety@springernature.com
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Germania

Altre edizioni note dello stesso titolo

9781013270871: IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency

Edizione in evidenza

ISBN 10:  1013270878 ISBN 13:  9781013270871
Casa editrice: Saint Philip Street Press, 2020
Rilegato