ONTOLOGICAL GRAPH BASED MODELLING AND SIMULATION

We examine the benefits of using an ontology and knowledge graph (KG) approach in developing and maintaining discrete-event simulation (DES) models. Ontologies provide a standardised language, enabling a structured representation of domain knowledge and enhancing model accuracy, reliability, and knowledge transfer. Ontologies applied in Knowledge Graphs represent physical assets and processes, enabling the integration of diverse data sources, maintaining the model’s relevance. Together, they enable the creation of digital twins to support advanced analytics and informed decision-making. In conjunction the Digital Twin Ontology (DTO) and Digital Twin Graph (DTG) form the foundation of a data model, providing a formalized language and digital representation of entities. Using Microsoft Azure Digital Twins (ADT), we enable automation of the development of a brewery process simulation, highlighting the benefits of ontologies and knowledge graphs for building and maintaining simulation models, ensuring accurate representations of physical assets and processes, and enabling use cases.