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Technologien für die intelligente Automation
Open Access This content is freely available online to anyone, anywhere at any time.

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

Intelligent Methods for the Factory of the Future

Editors: Niggemann, Oliver, Schüller, Peter (Eds.)

  • Provides engineering-lean, unsupervised methods that scale in realistic scenarios
  • Helps to improve reliability and efficiency of complex systems
  • Presents examples and results from real factories and real cyber-physical systems
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eBook  
  • ISBN 978-3-662-57805-6
  • This book is an open access book, you can download it for free on link.springer.com
Softcover $119.99
price for USA in USD
  • ISBN 978-3-662-57804-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

About the authors

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.




Table of contents (7 chapters)

  • Concept and Implementation of a Software Architecture for Unifying Data Transfer in Automated Production Systems

    Trunzer, Emanuel (et al.)

    Pages 1-17

  • Social Science Contributions to Engineering Projects: Looking Beyond Explicit Knowledge Through the Lenses of Social Theory

    Müller, Peter (et al.)

    Pages 19-36

  • Enable learning of Hybrid Timed Automata in Absence of Discrete Events through Self-Organizing Maps

    von Birgelen, Alexander (et al.)

    Pages 37-54

  • Anomaly Detection and Localization for Cyber-Physical Production Systems with Self-Organizing Maps

    von Birgelen, Alexander (et al.)

    Pages 55-71

  • A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes

    Windmann, Stefan (et al.)

    Pages 73-91

Buy this book

eBook  
  • ISBN 978-3-662-57805-6
  • This book is an open access book, you can download it for free on link.springer.com
Softcover $119.99
price for USA in USD
  • ISBN 978-3-662-57804-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency
Book Subtitle
Intelligent Methods for the Factory of the Future
Editors
  • Oliver Niggemann
  • Peter Schüller
Series Title
Technologien für die intelligente Automation
Series Volume
8
Copyright
2018
Publisher
Springer Vieweg
Copyright Holder
The Editor(s) (if applicable) and The Author(s)
eBook ISBN
978-3-662-57805-6
DOI
10.1007/978-3-662-57805-6
Softcover ISBN
978-3-662-57804-9
Series ISSN
2522-8579
Edition Number
1
Number of Pages
VII, 129
Number of Illustrations
23 b/w illustrations, 29 illustrations in colour
Topics