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7 CONCLUSIONS AND FUTURE
WORK
Interoperability of information is an essential prere-
quisite for efficient integration of data. This also ap-
plies to the complex domain of industrial processes
that typically are distributed and of large scale. This
paper presented message structures developed that are
needed to implement advanced plant-wide monitoring
and control solutions.
First, a comparison of existing standards was pre-
sented with some structures applicable for data ex-
change. Based on this, and utilising constructs from
these standards, message structures were proposed for
communicating data and events in industrial proces-
ses. The developed concepts were demonstrated with
use case examples. Although the examples were li-
mited by scope the concept can be scaled to larger
real-world industry settings.
In the future, the message structures could be ex-
perimented in the integration of actual production sy-
stems. In addition, new message structures will likely
be added. For instance, for schedules, the structures
of ANSI/ISA-95 will likely be utilised. The API li-
braries are work in progress that will facilitate taking
into use the proposed message structures.
ACKNOWLEDGEMENTS
This work has received funding from the European
Union’s Horizon 2020 research and innovation pro-
gramme under grant agreement No 723661. This
study reflects only the authors’ views, and the Com-
mission is not responsible for any use that may be
made of the information contained therein. The aut-
hors want to express their sincere gratitude to the
funder and the project partners in the COCOP pro-
ject (Coordinating Optimisation of Complex Indus-
trial Processes, https://www.cocop-spire.eu/ ).
In addition, the authors are grateful to the Aca-
demy of Finland for their funding (grant 310098).
REFERENCES
ANSI/ISA-88.00.01 (2010). ANSI/ISA-88.00.01-2010 Ba-
tch Control Part 1: Models and Terminology.
ANSI/ISA.
ANSI/ISA-95.00.01 (2010). ANSI/ISA-95.00.01-2010 (IEC
62264-1 Mod). Enterprise-Control System Integration
– Part 1: Models and Terminology. ISA, Research
Triangle Park, NC, USA.
Chemical Markup Language (2018). Chemical markup
language. http://www.xml-cml.org (accessed 7 Jun
2018).
Chungoora, N., Young, R. I., Gunendran, G., Palmer, C.,
Usman, Z., Anjum, N. A., Cutting-Decelle, A.-F.,
Harding, J. A., and Case, K. (2013). A model-driven
ontology approach for manufacturing system intero-
perability and knowledge sharing. Computers in In-
dustry, 64(4):392 – 401.
Dai, W., Dubinin, V., and Vyatkin, V. (2013). Auto-
matically generated layered ontological models for
semantic analysis of component-based control sys-
tems. IEEE Transactions on Industrial Informatics,
9(4):2124–2136.
Geography Markup Language (2007). Geography markup
language. http://www.opengeospatial.org/standards/
gml (accessed 7 Jun 2018).
Georgoudakis, M., Alexakos, C., Kalogeras, A., Gialelis,
J., and Koubias, S. (2006). Decentralized production
control through ansi / isa-95 based ontology and
agents. In Factory Communication Systems, 2006
IEEE International Workshop on, pages 374–379.
Graube, M., Pfeffer, J., Ziegler, J., and Urbas, L. (2011).
Linked data as integrating technology for industrial
data. In Network-Based Information Systems, 14th In-
ternational Conference on, pages 162–167.
H
¨
astbacka, D., Barna, L., Karaila, M., Liang, Y., Tuomi-
nen, P., and Kuikka, S. (2014). Device status infor-
mation service architecture for condition monitoring
using opc ua. In Proceedings of the 2014 IEEE Emer-
ging Technology and Factory Automation (ETFA), pa-
ges 1–7.
H
¨
astbacka, D. and Kuikka, S. (2013). Semantics enhanced
engineering and model reasoning for control applica-
tion development. Multimedia Tools and Applications,
65(1):47–62.
H
¨
astbacka, D., Jantunen, E., Karaila, M., and Barna, L.
(2016). Service-based condition monitoring for cloud-
enabled maintenance operations. In IECON 2016 -
42nd Annual Conference of the IEEE Industrial Elec-
tronics Society, pages 5289–5295.
Lamnabhi-Lagarrigue, F., Annaswamy, A., Engell, S., Is-
aksson, A., Khargonekar, P., Murray, R. M., Nijmeijer,
H., Samad, T., Tilbury, D., and den Hof, P. V. (2017).
Systems & control for the future of humanity, research
agenda: Current and future roles, impact and grand
challenges. Annual Reviews in Control, 43:1 – 64.
Lima, F., Li, S., Mirlekar, G., Sridhar, L., and Ruiz-
Mercado, G. (2016). Chapter five - modeling and ad-
vanced control for sustainable process systems. In
Ruiz-Mercado, G., , and Cabezas, H., editors, Sus-
tainability in the Design, Synthesis and Analysis of
Chemical Engineering Processes, pages 115 – 139.
Butterworth-Heinemann, Oxford.
Mu
˜
noz, E., Cap
´
on-Garc
´
ıa, E., Espu
˜
na, A., and Puigjaner,
L. (2012). Ontological framework for enterprise-wide
integrated decision-making at operational level. Com-
puters & Chemical Engineering, 42:217 – 234.
Observations and Measurements (2011). Observa-
tions and measurements. Version 2.0. http://
Information Models and Information Exchange in Plant-wide Monitoring and Control of Industrial Processes
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