IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency: Intelligent Methods for the Factory of the Future: 8 (Technologien für die intelligente Automation) - Tapa blanda

Libro 6 de 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 (Technologien für die intelligente Automation)
Tapa blanda
ISBN 10: 3662578042 ISBN 13: 9783662578049
Editorial: Springer Vieweg, 2018

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

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.




De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer Vieweg
Año de publicación
2018
Idioma
Inglés
ISBN 10 
3662578042
ISBN 13 
9783662578049
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
140
Editor
Niggemann Oliver, Schüller Peter
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Alemania

Otras ediciones populares con el mismo título

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

Edición Destacada

ISBN 10:  1013270878 ISBN 13:  9781013270871
Editorial: Saint Philip Street Press, 2020
Tapa dura