---
_id: '12800'
abstract:
- lang: eng
text: his paper presents the cognitive module of the Cognitive Architecture for
Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The
goal of this architecture is to reduce the implementation effort of artificial
intelligence (AI) algorithms in CPPS. Declarative user goals and the provided
algorithm-knowledge base allow the dynamic pipeline orchestration and configuration.
A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance
for further evaluation through the cognitive module. Thus, the cognitive module
is able to select feasible and robust configurations for process pipelines in
varying use cases. Furthermore, it automatically adapts the models and algorithms
based on model quality and resource consumption. The cognitive module also instantiates
additional pipelines to evaluate algorithms from different classes on test functions.
CAAI relies on well-defined interfaces to enable the integration of additional
modules and reduce implementation effort. Finally, an implementation based on
Docker, Kubernetes, and Kafka for the virtualization and orchestration of the
individual modules and as messaging technology for module communication is used
to evaluate a real-world use case.
author:
- first_name: Jan
full_name: Strohschein, Jan
last_name: Strohschein
- first_name: Andreas
full_name: Fischbach, Andreas
last_name: Fischbach
- first_name: Andreas
full_name: Bunte, Andreas
id: '58885'
last_name: Bunte
- first_name: Heide
full_name: Faeskorn-Woyke, Heide
last_name: Faeskorn-Woyke
- first_name: Natalia
full_name: Moriz, Natalia
id: '44238'
last_name: Moriz
- first_name: Thomas
full_name: Bartz-Beielstein, Thomas
last_name: Bartz-Beielstein
citation:
ama: Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein
T. Cognitive capabilities for the CAAI in cyber-physical production systems. The
International Journal of Advanced Manufacturing Technology. 2021;115(11-12):3513-3532.
doi:10.1007/s00170-021-07248-3
apa: Strohschein, J., Fischbach, A., Bunte, A., Faeskorn-Woyke, H., Moriz, N., &
Bartz-Beielstein, T. (2021). Cognitive capabilities for the CAAI in cyber-physical
production systems. The International Journal of Advanced Manufacturing Technology,
115(11–12), 3513–3532. https://doi.org/10.1007/s00170-021-07248-3
bjps: Strohschein J et al. (2021) Cognitive Capabilities for the CAAI
in Cyber-Physical Production Systems. The International Journal of Advanced
Manufacturing Technology 115, 3513–3532.
chicago: 'Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke,
Natalia Moriz, and Thomas Bartz-Beielstein. “Cognitive Capabilities for the CAAI
in Cyber-Physical Production Systems.” The International Journal of Advanced
Manufacturing Technology 115, no. 11–12 (2021): 3513–32. https://doi.org/10.1007/s00170-021-07248-3.'
chicago-de: 'Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke,
Natalia Moriz und Thomas Bartz-Beielstein. 2021. Cognitive capabilities for the
CAAI in cyber-physical production systems. The International Journal of Advanced
Manufacturing Technology 115, Nr. 11–12: 3513–3532. doi:10.1007/s00170-021-07248-3,
.'
din1505-2-1: 'Strohschein, Jan ; Fischbach, Andreas ; Bunte,
Andreas ; Faeskorn-Woyke, Heide
; Moriz, Natalia ; Bartz-Beielstein,
Thomas: Cognitive capabilities for the CAAI in cyber-physical production
systems. In: The International Journal of Advanced Manufacturing Technology
Bd. 115. London [u.a.], Springer (2021), Nr. 11–12, S. 3513–3532'
havard: J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T.
Bartz-Beielstein, Cognitive capabilities for the CAAI in cyber-physical production
systems, The International Journal of Advanced Manufacturing Technology. 115 (2021)
3513–3532.
ieee: 'J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, and
T. Bartz-Beielstein, “Cognitive capabilities for the CAAI in cyber-physical production
systems,” The International Journal of Advanced Manufacturing Technology,
vol. 115, no. 11–12, pp. 3513–3532, 2021, doi: 10.1007/s00170-021-07248-3.'
mla: Strohschein, Jan, et al. “Cognitive Capabilities for the CAAI in Cyber-Physical
Production Systems.” The International Journal of Advanced Manufacturing Technology,
vol. 115, no. 11–12, 2021, pp. 3513–32, https://doi.org/10.1007/s00170-021-07248-3.
short: J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein,
The International Journal of Advanced Manufacturing Technology 115 (2021) 3513–3532.
ufg: 'Strohschein, Jan u. a.: Cognitive capabilities for the CAAI in cyber-physical
production systems, in: The International Journal of Advanced Manufacturing
Technology 115 (2021), H. 11–12, S. 3513–3532.'
van: Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein
T. Cognitive capabilities for the CAAI in cyber-physical production systems. The
International Journal of Advanced Manufacturing Technology. 2021;115(11–12):3513–32.
date_created: 2025-04-15T13:05:17Z
date_updated: 2025-06-26T13:39:22Z
department:
- _id: DEP5023
doi: 10.1007/s00170-021-07248-3
external_id:
isi:
- '000659025000010'
intvolume: ' 115'
isi: '1'
issue: 11-12
keyword:
- Cognition
- Industry 40
- Big data platform
- Machine learning
- CPPS
- Optimization
- Algorithm selection
- Simulation
language:
- iso: eng
page: 3513-3532
place: London [u.a.]
publication: The International Journal of Advanced Manufacturing Technology
publication_identifier:
eissn:
- 1433-3015
issn:
- 0268-3768
publication_status: published
publisher: 'Springer '
status: public
title: Cognitive capabilities for the CAAI in cyber-physical production systems
type: scientific_journal_article
user_id: '83781'
volume: 115
year: '2021'
...
---
_id: '4518'
abstract:
- lang: eng
text: This paper introduces CAAI, a novel cognitive architecture for artificial
intelligence in cyber-physical production systems. The goal of the architecture
is to reduce the implementation effort for the usage of artificial intelligence
algorithms. The core of the CAAI is a cognitive module that processes the user's
declarative goals, selects suitable models and algorithms, and creates a configuration
for the execution of a processing pipeline on a big data platform. Constant observation
and evaluation against performance criteria assess the performance of pipelines
for many and different use cases. Based on these evaluations, the pipelines are
automatically adapted if necessary. The modular design with well-defined interfaces
enables the reusability and extensibility of pipeline components. A big data platform
implements this modular design supported by technologies such as Docker, Kubernetes,
and Kafka for virtualization and orchestration of the individual components and
their communication. The implementation of the architecture is evaluated using
a real-world use case. The prototypic implementation is accessible on GitHub and
contains a demonstration.
author:
- first_name: Andreas
full_name: Fischbach, Andreas
last_name: Fischbach
- first_name: Jan
full_name: Strohschein, Jan
last_name: Strohschein
- first_name: Andreas
full_name: Bunte, Andreas
id: '58885'
last_name: Bunte
- first_name: Jörg
full_name: Stork, Jörg
last_name: Stork
- first_name: Heide
full_name: Faeskorn-Woyke, Heide
last_name: Faeskorn-Woyke
- first_name: Natalia
full_name: Moriz, Natalia
id: '44238'
last_name: Moriz
- first_name: Thomas
full_name: Bartz-Beielstein, Thomas
last_name: Bartz-Beielstein
citation:
ama: Fischbach A, Strohschein J, Bunte A, et al. CAAI -- A Cognitive Architecture
to Introduce Artificial Intelligence in Cyber-Physical Production Systems. The
International Journal of Advanced Manufacturing Technology. 2020;111(1/2):609-626.
doi:10.1007/s00170-020-06094-z
apa: Fischbach, A., Strohschein, J., Bunte, A., Stork, J., Faeskorn-Woyke, H., Moriz,
N., & Bartz-Beielstein, T. (2020). CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems. The International
Journal of Advanced Manufacturing Technology, 111(1/2), 609–626. https://doi.org/10.1007/s00170-020-06094-z
bjps: Fischbach A et al. (2020) CAAI -- A Cognitive Architecture to
Introduce Artificial Intelligence in Cyber-Physical Production Systems. The
International Journal of Advanced Manufacturing Technology 111, 609–626.
chicago: 'Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide
Faeskorn-Woyke, Natalia Moriz, and Thomas Bartz-Beielstein. “CAAI -- A Cognitive
Architecture to Introduce Artificial Intelligence in Cyber-Physical Production
Systems.” The International Journal of Advanced Manufacturing Technology
111, no. 1/2 (2020): 609–26. https://doi.org/10.1007/s00170-020-06094-z.'
chicago-de: 'Fischbach, Andreas, Jan Strohschein, Andreas Bunte, Jörg Stork, Heide
Faeskorn-Woyke, Natalia Moriz und Thomas Bartz-Beielstein. 2020. CAAI -- A Cognitive
Architecture to Introduce Artificial Intelligence in Cyber-Physical Production
Systems. The International Journal of Advanced Manufacturing Technology
111, Nr. 1/2: 609–626. doi:10.1007/s00170-020-06094-z,
.'
din1505-2-1: 'Fischbach, Andreas ;
Strohschein, Jan ; Bunte,
Andreas ; Stork, Jörg ; Faeskorn-Woyke, Heide ; Moriz,
Natalia ; Bartz-Beielstein, Thomas:
CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems. In: The International Journal of Advanced Manufacturing
Technology Bd. 111, Springer (2020), Nr. 1/2, S. 609–626'
havard: A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N.
Moriz, T. Bartz-Beielstein, CAAI -- A Cognitive Architecture to Introduce Artificial
Intelligence in Cyber-Physical Production Systems, The International Journal of
Advanced Manufacturing Technology. 111 (2020) 609–626.
ieee: 'A. Fischbach et al., “CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems,” The International
Journal of Advanced Manufacturing Technology, vol. 111, no. 1/2, pp. 609–626,
2020, doi: 10.1007/s00170-020-06094-z.'
mla: Fischbach, Andreas, et al. “CAAI -- A Cognitive Architecture to Introduce Artificial
Intelligence in Cyber-Physical Production Systems.” The International Journal
of Advanced Manufacturing Technology, vol. 111, no. 1/2, 2020, pp. 609–26,
https://doi.org/10.1007/s00170-020-06094-z.
short: A. Fischbach, J. Strohschein, A. Bunte, J. Stork, H. Faeskorn-Woyke, N. Moriz,
T. Bartz-Beielstein, The International Journal of Advanced Manufacturing Technology
111 (2020) 609–626.
ufg: 'Fischbach, Andreas u. a.: CAAI -- A Cognitive Architecture to Introduce
Artificial Intelligence in Cyber-Physical Production Systems, in: The International
Journal of Advanced Manufacturing Technology 111 (2020), H. 1/2, S. 609–626.'
van: Fischbach A, Strohschein J, Bunte A, Stork J, Faeskorn-Woyke H, Moriz N, et
al. CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems. The International Journal of Advanced Manufacturing Technology.
2020;111(1/2):609–26.
date_created: 2021-01-26T12:24:10Z
date_updated: 2025-06-26T13:38:24Z
department:
- _id: DEP5023
doi: 10.1007/s00170-020-06094-z
external_id:
isi:
- '000574389900002'
intvolume: ' 111'
isi: '1'
issue: 1/2
keyword:
- CPPS
- Artificial intelligence
- Industry 40
- Reference architecture
- Optimization
- SMBO
- Cognition
- Big data platform
- Modularization
- AutoML
language:
- iso: eng
page: 609-626
publication: The International Journal of Advanced Manufacturing Technology
publication_identifier:
eissn:
- 1433-3015
issn:
- 0268-3768
publication_status: published
publisher: Springer
status: public
title: CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical
Production Systems
type: journal_article
user_id: '83781'
volume: 111
year: '2020'
...
---
_id: '4336'
abstract:
- lang: eng
text: "Prolonged life expectancy along with the increasing complexity of medicine
and health services raises health costs worldwide dramatically. Whilst the smart
health concept has much potential to support the concept of the emerging P4-medicine
(preventive, participatory, predictive, and personalized), such high-tech medicine
produces large amounts of high-dimensional, weakly-structured data sets and massive
amounts of unstructured information. All these technological approaches along
with “big data” are turning the medical sciences into a data-intensive science.
To keep pace with the growing amounts of complex data, smart hospital approaches
are a commandment of the future, necessitating context aware computing along with
advanced interaction paradigms in new physical-digital ecosystems.\r\n\r\nThe
very successful synergistic combination of methodologies and approaches from Human-Computer
Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions
for the vision to support human intelligence with machine learning.\r\n\r\nThe
papers selected for this volume focus on hot topics in smart health; they discuss
open problems and future challenges in order to provide a research agenda to stimulate
further research and progress."
citation:
ama: 'Holzinger A, Röcker C, Ziefle M, eds. Smart Health: Open Problems and Future
Challenges. Vol 8700. Heidelberg: Springer; 2015. doi:10.1007/978-3-319-16226-3'
apa: 'Holzinger, A., Röcker, C., & Ziefle, M. (Eds.). (2015). Smart Health:
Open Problems and Future Challenges (Vol. 8700). Heidelberg: Springer. https://doi.org/10.1007/978-3-319-16226-3'
bjps: 'Holzinger A, Röcker C and Ziefle M (eds) (2015) Smart Health: Open
Problems and Future Challenges. Heidelberg: Springer.'
chicago: 'Holzinger, Andreas, Carsten Röcker, and Martina Ziefle, eds. Smart
Health: Open Problems and Future Challenges. Vol. 8700. Lecture Notes in Computer
Science / Information Systems and Applications, Incl. Internet/Web, and HCI.
Heidelberg: Springer, 2015. https://doi.org/10.1007/978-3-319-16226-3.'
chicago-de: 'Holzinger, Andreas, Carsten Röcker und Martina Ziefle, Hrsg. 2015.
Smart Health: Open Problems and Future Challenges. Bd. 8700. Lecture Notes
in Computer Science / Information Systems and Applications, incl. Internet/Web,
and HCI. Heidelberg: Springer. doi:10.1007/978-3-319-16226-3,
.'
din1505-2-1: 'Holzinger, A. ; Röcker, C. ; Ziefle,
M. (Hrsg.): Smart Health: Open Problems and Future Challenges, Lecture
Notes in Computer Science / Information Systems and Applications, incl. Internet/Web,
and HCI. Bd. 8700. Heidelberg : Springer, 2015'
havard: 'A. Holzinger, C. Röcker, M. Ziefle, eds., Smart Health: Open Problems and
Future Challenges, Springer, Heidelberg, 2015.'
ieee: 'A. Holzinger, C. Röcker, and M. Ziefle, Eds., Smart Health: Open Problems
and Future Challenges, vol. 8700. Heidelberg: Springer, 2015.'
mla: 'Holzinger, Andreas, et al., editors. Smart Health: Open Problems and Future
Challenges. Vol. 8700, Springer, 2015, doi:10.1007/978-3-319-16226-3.'
short: 'A. Holzinger, C. Röcker, M. Ziefle, eds., Smart Health: Open Problems and
Future Challenges, Springer, Heidelberg, 2015.'
ufg: 'Holzinger, Andreas et. al. (Hgg.) (2015): Smart Health: Open Problems
and Future Challenges (=Lecture Notes in Computer Science / Information Systems
and Applications, incl. Internet/Web, and HCI 8700), Heidelberg.'
van: 'Holzinger A, Röcker C, Ziefle M, editors. Smart Health: Open Problems and
Future Challenges. Heidelberg: Springer; 2015. 275 p. (Lecture Notes in Computer
Science / Information Systems and Applications, incl. Internet/Web, and HCI;
vol. 8700).'
date_created: 2021-01-08T12:03:52Z
date_updated: 2023-03-15T13:49:52Z
department:
- _id: DEP5023
doi: 10.1007/978-3-319-16226-3
editor:
- first_name: Andreas
full_name: Holzinger, Andreas
last_name: Holzinger
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
- first_name: Martina
full_name: Ziefle, Martina
last_name: Ziefle
intvolume: ' 8700'
keyword:
- HCI
- ambient assisted living
- big data
- computational intelligence
- context awareness
- data centric medicine
- decision support
- interactive data mining
- keyword detection
- knoweldge bases
- knoweldge discovery
- machine learning
- medical decision support
- medical informatics
- natural language processing
- pervasive health
- smart home
- ubiquitous computing
- visualization
- wearable sensors
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'http://www.springerlink.com/content/978-3-319-16226-3 '
oa: '1'
page: '275'
place: Heidelberg
publication_identifier:
eisbn:
- 978-3-319-16226-3
eissn:
- 1611-3349
isbn:
- 978-3-319-16225-6
issn:
- 0302-9743
publication_status: published
publisher: Springer
series_title: Lecture Notes in Computer Science / Information Systems and Applications,
incl. Internet/Web, and HCI
status: public
title: 'Smart Health: Open Problems and Future Challenges'
type: book_editor
user_id: '15514'
volume: 8700
year: 2015
...
---
_id: '2102'
abstract:
- lang: ger
text: Die Zustandsüberwachung erfolgt derzeit in der Regel durch Einsatz spezieller Sensorik,
bspw. durch Vibrationsmessungen. Außerdem werden die Antriebe lediglich isoliert
betrachtet, eine Zusammenführung anfallender Informationen eines räumlich verteilten Antriebsverbunds findet meist
nicht statt. Im Folgenden wird ein neuartiges Motor-as-Sensor-Konzept vorgeschlagen
und validiert, das eine antizipatorische Zustandsüberwachung ohne Einsatz zusätzlicher
Sensorik allein durch Verarbeitung der phasenbezogenen Motorströme ermöglicht. Zusätzlich wird ein Informationsfusionskonzept vorge-stellt,
das die Informationen aller im Verbund beteiligten Antriebe zusammenführt, um
darüber eine mit weniger Unsicherheiten behaftete Aussage über den Zustand einer
Ap-plikation herbeizuführen. Das Hauptaugenmerk liegt hierbei insbesondere auf der Beherrschung der anfallenden riesigen Datenmengen, die zur Verarbeitung in eingebetteten
Systemen reduziert werden müssen.
author:
- first_name: Karl
full_name: Voth, Karl
last_name: Voth
- first_name: Alexander
full_name: Dicks, Alexander
id: '1853'
last_name: Dicks
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Voth K, Dicks A, Lohweg V. Konfliktlösende Informationsfusion zur Maschinendiagnose
am Beispiel von Extrusionsanlagen, 21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 30. November - 02. Dezember 2011, Dortmund.
In: ; 2011.'
apa: Voth, K., Dicks, A., & Lohweg, V. (2011). Konfliktlösende Informationsfusion
zur Maschinendiagnose am Beispiel von Extrusionsanlagen, 21. Workshop Computational
Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), 30.
November - 02. Dezember 2011, Dortmund.
bjps: Voth K, Dicks A and Lohweg V (2011) Konfliktlösende Informationsfusion
zur Maschinendiagnose am Beispiel von Extrusionsanlagen, 21. Workshop Computational
Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), 30.
November - 02. Dezember 2011, Dortmund.
chicago: Voth, Karl, Alexander Dicks, and Volker Lohweg. “Konfliktlösende Informationsfusion
zur Maschinendiagnose am Beispiel von Extrusionsanlagen, 21. Workshop Computational
Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), 30.
November - 02. Dezember 2011, Dortmund,” 2011.
chicago-de: 'Voth, Karl, Alexander Dicks und Volker Lohweg. 2011. Konfliktlösende
Informationsfusion zur Maschinendiagnose am Beispiel von Extrusionsanlagen, 21.
Workshop Computational Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik
(GMA), 30. November - 02. Dezember 2011, Dortmund. In: .'
din1505-2-1: 'Voth, Karl ; Dicks,
Alexander ; Lohweg, Volker:
Konfliktlösende Informationsfusion zur Maschinendiagnose am Beispiel von Extrusionsanlagen,
21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik
(GMA), 30. November - 02. Dezember 2011, Dortmund. In: , 2011'
havard: 'K. Voth, A. Dicks, V. Lohweg, Konfliktlösende Informationsfusion zur Maschinendiagnose
am Beispiel von Extrusionsanlagen, 21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 30. November - 02. Dezember 2011, Dortmund,
in: 2011.'
ieee: K. Voth, A. Dicks, and V. Lohweg, “Konfliktlösende Informationsfusion zur
Maschinendiagnose am Beispiel von Extrusionsanlagen, 21. Workshop Computational
Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), 30.
November - 02. Dezember 2011, Dortmund,” 2011.
mla: Voth, Karl, et al. Konfliktlösende Informationsfusion zur Maschinendiagnose
am Beispiel von Extrusionsanlagen, 21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 30. November - 02. Dezember 2011, Dortmund.
2011.
short: 'K. Voth, A. Dicks, V. Lohweg, in: 2011.'
ufg: 'Voth, Karl et. al. (2011): Konfliktlösende Informationsfusion zur Maschinendiagnose
am Beispiel von Extrusionsanlagen, 21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 30. November - 02. Dezember 2011, Dortmund,
in: .'
van: Voth K, Dicks A, Lohweg V. Konfliktlösende Informationsfusion zur Maschinendiagnose
am Beispiel von Extrusionsanlagen, 21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 30. November - 02. Dezember 2011, Dortmund.
In 2011.
date_created: 2019-12-02T14:32:58Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
keyword:
- Sensor- und Informationsfusion
- elektrischer Antrieb
- Cyber-Physical System
- Industrie 4.0
- Big Data
language:
- iso: ger
publication_status: published
status: public
title: Konfliktlösende Informationsfusion zur Maschinendiagnose am Beispiel von Extrusionsanlagen,
21. Workshop Computational Intelligence, VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik
(GMA), 30. November - 02. Dezember 2011, Dortmund
type: conference
user_id: '45673'
year: 2011
...