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R. Sindelar, P. Novak:
"Ontology-based simulation design and integration";
in: "Semantic Web for Intelligent Engineering Applications", Springer International Publishing Switzerland, 2016, ISBN: 978-3-319-41488-1, 257 - 277.

Strict requirements on the quality of industrial plant operation together
with environmental limits and the pursuit of decreasing energy consumption bring
more complexity in automation systems. Simulations and models of industrial
processes can be utilized in all the phases of an automation system´s life cycle and
they can be used for process design as well as for optimal plant operation. Present
methods of design and integration of simulations tasks are inefficient and error-prone
because almost all pieces of information and knowledge are handled manually. In
this chapter, we describe a simulation framework where all configurations, simulation
tasks, and scenarios are obtained from a common knowledge base. The knowledge
base is implemented utilizing an ontology for defining a data model to represent
real-world concepts, different engineering knowledge as well as descriptions
and relations to other domains. Ontologies allow the capturing of structural changes
in simulations and evolving simulation scenarios more easily than using standard
relational databases. Natively ontologies are used to represent the knowledge shared
between different projects and systems. The simulation framework provides tools
for efficient integration of data and simulations by exploiting the advantages of formalized
knowledge. Two processes utilizing Semantic Web technologies within the
simulation framework are presented at the end of this chapter.

Simulation design ⋅ SCADA ⋅ Model-driven design ⋅ Complex simulations ⋅ Knowledge integration

http://dx.doi.org/10.1007/978-3-319-41490-4