# Ontology-Based Production Simulation with OntologySim
## 4 Proposed Ontology-Based Simulation
### Unique Selling Proposition (USP)  
Figure 6 summarizes the main points of differentiation from other simulations. The individual contents of the framework are explained in more detail in the various chapters: Sections 5-7. The USP is based on the following advantages over existing discrete-event simulations:  
* _Saving, Loading of Simulation:_ Interrupting the simulation during runtime enables new use cases and possibilities, which are shown in Figure 7. When saving the simulation, the current state of the ontology is stored in a single OWL file. This saved data is sufficient to restart the simulation, as all essential information is contained in the ontology. In particular, the following new use cases are enabled:
* The stored image can be run on other computational units and enables the easy extraction of information data. * After saving a defined state, several strategies, multi-agents, etc., can simulate different simulation runs, and the best agent configuration can be selected to facilitate research in this domain [31; 55; 58]. * Furthermore, time saving is achieved because the initial run-up and warm-up of a simulation into a static state can be skipped, as a static stimulation can be loaded, that is \"identical\" to the real system state to increase inference accuracy required for real-world use cases [59; 60]. * A real world digital twin is enabled, as up-to-the-minute virtual models can be started with the exact same initial situation [3]. Figure 6: Unique position of the simulation. * _Extendable during simulation run:_ Saving and loading the simulation provides the basis for the simulation to be extended during a run. In addition to changing the strategy, adjustments can also be made to the manufacturing system which affect resources, such as machines, transporters, or processes. Thus, for example, transporters can be removed or added, or process times can be changed. It is also possible to add data and information that is not needed currently for the simulation. By adding supplementary nodes, it is possible to link external (real-world) data or to model the current description in detail. An example would be the addition of installation space sizes for the product, novel products added to the portfolio [33], or changes in the shopfloor management, as well as increased worker competencies [61]. * _Extendable open source application:_ Another advantage compared to the majority of simulations reviewed in Section 3 is that OntologySim is implemented with the basic idea of being an open-source publication and software. Thus, the focus of the implementation is to make the simulation easily adaptable and to provide clearly defined and explained interfaces. This makes it possible to simply extend the simulation with self-implemented agents and access the ontology through standardized wrapper methods. * _Generalization:_ The interaction of the ontology and the Python modules enables a good generalization of simulation models. It is possible to model different production systems, be it line production, a workshop production or matrix production, or any combination. The ontology can be extended and customized to meet specific requirements. This includes the possible integration of information about tangible objects, such as products, intangible information, such as production planning, and control organization [33; 58], or ever-changing, human-centered Industry 4.0 implementations [61]. * _Step wise going back in simulation:_ Going back within a single simulation run in a step-by-step manner is another special feature of the OntologySim. Going back enables a better analysis of the simulation and increases the traceability and understanding of complex production systems [60]. This feature is made possible by the fact that, at any point in time, a defined state is available, and the past events are stored. These two properties are sufficient to recreate the past and explicitly analyze its states. By doing so, the analysis of \"what  
Figure 7: Use cases for saving and loading simulation.