Coverart for item
The Resource IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future, edited by Oliver Niggemann, Peter Schüller, (electronic resource)

IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future, edited by Oliver Niggemann, Peter Schüller, (electronic resource)

Label
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future
Title
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency
Title remainder
Intelligent Methods for the Factory of the Future
Statement of responsibility
edited by Oliver Niggemann, Peter Schüller
Contributor
Editor
Provider
Subject
Language
eng
Summary
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
Member of
Image bit depth
0
LC call number
  • TA169.7
  • T55-T55.3
  • TA403.6
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
  • Niggemann, Oliver.
  • Schüller, Peter.
  • SpringerLink
Series statement
Technologien für die intelligente Automation, Technologies for Intelligent Automation,
Series volume
8
http://library.link/vocab/subjectName
  • Engineering
  • Computer input-output equipment
  • Robotics
  • Automation
  • Quality control
  • Reliability
  • Industrial safety
  • Engineering
  • Quality Control, Reliability, Safety and Risk
  • Robotics and Automation
  • Input/Output and Data Communications
Label
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future, edited by Oliver Niggemann, Peter Schüller, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Concept and Implementation of a Software Architecture for Unifying Data Transfer in Automated Production Systems -- Social Science Contributions to Engineering Projects: Looking Beyond Explicit Knowledge Through the Lenses of Social Theory -- Enable learning of Hybrid Timed Automata in Absence of Discrete Events through Self-Organizing Maps -- Anomaly Detection and Localization for Cyber-Physical Production Systems with Self-Organizing Maps -- A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes -- Validation of similarity measures for industrial alarm flood analysis -- Concept for Alarm Flood Reduction with Bayesian Networks by Identifying the Root Cause
Dimensions
unknown
Extent
VII, 129 p. 52 illus., 29 illus. in color.
File format
multiple file formats
Form of item
electronic
Governing access note
Open Access
Isbn
9783662578056
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-662-57805-6
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-662-57805-6
Label
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency : Intelligent Methods for the Factory of the Future, edited by Oliver Niggemann, Peter Schüller, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Concept and Implementation of a Software Architecture for Unifying Data Transfer in Automated Production Systems -- Social Science Contributions to Engineering Projects: Looking Beyond Explicit Knowledge Through the Lenses of Social Theory -- Enable learning of Hybrid Timed Automata in Absence of Discrete Events through Self-Organizing Maps -- Anomaly Detection and Localization for Cyber-Physical Production Systems with Self-Organizing Maps -- A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes -- Validation of similarity measures for industrial alarm flood analysis -- Concept for Alarm Flood Reduction with Bayesian Networks by Identifying the Root Cause
Dimensions
unknown
Extent
VII, 129 p. 52 illus., 29 illus. in color.
File format
multiple file formats
Form of item
electronic
Governing access note
Open Access
Isbn
9783662578056
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-662-57805-6
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-662-57805-6

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