Contributions to Proceedings:
C. Huemer, G. Kappel, M. Wimmer, H. Proper, S. Reich, W. Behrendt, S. Thalmann, G. Weichhart, A. Zoitl:
"Interoperability and Integration in Future Production Systems";
in: "2018 IEEE 20th Conference on Business Informatics (CBI)",
issued by: IEEE Computer Society;
IEEE Computer Society,
Los Alamitos,
2018, (invited),
ISBN: 978-1-5386-7016-3,
175
- 177.
English abstract:
Research in areas of Internet of Things (IoT), Industry 4.0 (I4.0), Cyber Physical Systems (CPS), consider system-of-systems composed of hardware and software systems that seamless work together. Interoperability ranges from compatibility (systems do not disturb other systems, but no interaction between systems) to integration (systems that share a common model/worldview). Between these extremes a continuum of interoperability exists.
In any case, interoperability is a model-driven approach - in contrast to data-driven or machine-learning approaches, for example. In general, models contain modules, connections, and behavior descriptions of different types.
Integration and interoperability may not only be seen as (goal) states but also as processes. Changes in one system might trigger adaptation in other systems. However, in loose integration and interoperability settings there is more support for the evolution of models.
German abstract:
Research in areas of Internet of Things (IoT), Industry 4.0 (I4.0), Cyber Physical Systems (CPS), consider system-of-systems composed of hardware and software systems that seamless work together. Interoperability ranges from compatibility (systems do not disturb other systems, but no interaction between systems) to integration (systems that share a common model/worldview). Between these extremes a continuum of interoperability exists.
In any case, interoperability is a model-driven approach - in contrast to data-driven or machine-learning approaches, for example. In general, models contain modules, connections, and behavior descriptions of different types.
Integration and interoperability may not only be seen as (goal) states but also as processes. Changes in one system might trigger adaptation in other systems. However, in loose integration and interoperability settings there is more support for the evolution of models.
Keywords:
Interoperability , Business , Production systems , Standards , Ontologies , Informatics
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/CBI.2018.10067
Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_276759.pdf
Created from the Publication Database of the Vienna University of Technology.