Why Using Ontologies In Process Modelling

Designing and operating a plant makes extensive use of process models. Currently the computational tools used for these activities are segmented into approximately five vertical domains: design, control design, identification, monitoring, and optimization. In each domain, methods are reasonably mature and good tools are available, but the domains are disconnected and since there are many overlaps in the form of models, methods and algorithms, individual tasks in the respective domains require similar efforts multiple times. More concrete, models are built, identified, validated and improved on a case-to-case base and for each operation in design, operation and control separately, which makes the overall engineering process extremely expensive and time consuming.

Ontology-based modelling makes it possible to generate model component libraries that are internally consistant satisfying the concept defined in the ontology. Controlling the combination of model components using the same ontology guarantees also composite models to satisfy the same concepts. This mechanism yields process models that satisfy the basic principles such as the conservation principles, transport phenomena and physical-chemical principles. Adding the ability to also handle order-of-magnitude assumptions in the same framework provides the means to generate multi-facetted model libraries for the same process covering different domains of application, thus integrating the now separated computational domains and providing across-the-board consistancy in the model-based computation engineering activities associated with all aspects of design and operation of a plant.