Editors:
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
Part of the book series: Technologien für die intelligente Automation (TIA, volume 8)
Buying options
Table of contents (7 chapters)
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Front Matter
About this book
Keywords
- Factory Automation
- Machine reliability and efficiency
- Cyber-physical systems
- Machine Learning
- Simulation & optimization
- Condition monitoring
- Alarm management
- Quality prediction
- Lean Engineering
- Open Access
- quality control, reliability, safety and risk
Editors and Affiliations
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inIT - Institut für industrielle Informationstechnik, Hochschule Ostwestfalen-Lippe, Lemgo, Germany
Oliver Niggemann
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Institut für Logic and Computation, Vienna University of Technology, Wien, Austria
Peter Schüller
About the editors
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
DOI: https://doi.org/10.1007/978-3-662-57805-6
Publisher: Springer Vieweg Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2018
License: CC BY
Softcover ISBN: 978-3-662-57804-9Published: 31 August 2018
eBook ISBN: 978-3-662-57805-6Published: 20 August 2018
Series ISSN: 2522-8579
Series E-ISSN: 2522-8587
Edition Number: 1
Number of Pages: VII, 129
Number of Illustrations: 23 b/w illustrations, 29 illustrations in colour
Topics: Security Science and Technology, Control, Robotics, Automation, Input/Output and Data Communications