Simulation is widely used to design and optimize manufacturing systems. However, the
creation of simulation models becomes a very complicated task when the system under study
has a high number of elements and interconnections between them. This is why simulation is
complex and time-consuming in the case of global production networks (GPNs). This type of
manufacturing network is used nowadays by companies of any size, but the complexity of the
material and information flows, which occur throughout a large number of production sites,
implies that it is difficult to achieve their full potential. Therefore, the need for improving the
current methods for creating simulation models arises. This way the simulation of global
production networks will be more accessible regarding the required time and cost and this will
allow the improvement of the design and operation of such networks. Ontologies represent
domains by describing concepts (classes) from the domain and the relations between them.
Among the wide variety of their applications, they have been used to represent processes from
manufacturing systems, as they present the information in a structured way and with a defined
terminology that supports the interoperability of different applications. This thesis proposes a
method that uses these ontologies to identify simulation modules that can be later implemented
in a simulation software. The method is based on the examination of the ontology classes to
identify the modules and on defining the interfaces between them by looking at the ontology
relations. The method is later applied for an ontology that models the order processing in
GPNs, in order to identify and develop general simulation modules. The resulting modules
facilitate the creation of simulation models by grouping several functions and avoiding the
repetitive task that would imply modelling these functions separately. Another advantage of
the modules is that they are reusable for different cases of GPNs. Finally, the general modules
have been instantiated for specific examples to prove that they allow the representation of the
systems in a valid way.
