An ontology for distributed process supervision of large-scale chemical plants

As modern chemical processes evolve into extremely large and complex systems involving multiple third-party technologies, instruments, and software, the information necessary for process supervision is distributed across disparate sources. Supervision methods rely on models that are themselves based on these process descriptors. Therefore, any changes during operations have to be reflected to the supervision methods so that they can adapt suitably. In this paper, we propose an ontology, called OntoSafe, that provides the semantics for abnormal situation management. It enables the integration of all the information necessary for forming a cohesive judgment of the condition and state of the process. It also captures the underlying linkages so that changes in the process descriptors are propagated consistently. We illustrate the benefits of these using the ENCORE distributed intelligence system. The application to an offshore oil and gas production case study is also reported.

► An ontology has been developed for process supervision methods.
► OntoSafe introduces concepts, classes and relations for formally representing the state and condition of a plant.
► OntoSafe adds a new aspect to OntoCAPE, and is linked to its concepts for describing the process, flowsheet, and models.
► The key benefit of incorporating semantics is that it enables changes in the process information to be reflected automatically to the process supervision methods.