A knowledge-driven approach for process supervision in chemical plants

In this work, an ontology-based framework for process supervision in chemical plants is presented. A conceptualization of equipment, control systems and hazards has been developed. This conceptual model includes the semantic of each modeled term in order to obtain a heavyweight ontology. The ontology has been formalized using Description Logic (DL) (Krotzsch et al., 2012). A knowledge-driven approach has been adopted in order to demonstrate how DL reasoning could be used to support process supervision, detecting and diagnosing faults, without the help of external agents. In the proposed approach, a DL reasoner adds implicit facts to the ontology through forward chaining reasoning, from the current measurements to the characterization of hazards. Additionally, the system is able to check knowledge consistency and formally explain the obtained results. The system functionality has been illustrated in the Tennessee Eastman process. benchmark. (C) 2013 Elsevier Ltd. All rights reserved.