An industry-oriented ontology-based knowledge model for batch process automation

Automation systems commonly consist of heterogeneous hardware as well as software. Changes of the production infrastructure, due to new product innovations or alternating market demands, lead to updates of the systems and services, which may require extensive engineering time and costs. In this context, the application of semantic technologies increases the flexibility of software solutions by enhancing the data integration. This paper introduces an ontology-based knowledge model for the batch process domain to achieve a semantic data model for vertical and horizontal data integration. An important asset of this knowledge representation is the consideration of industrial standards and thus its applicability in conjunction with a commercial supervisory control and data acquisition system. A practical use-case is presented that employs this ontology for automatically generating an application in zenon.