Semantic business analytics in industrial facilities - a case study

Abstract

In the following article we point out the potentials of semantic technologies for an application in the area of business analytics. Semantic Business Analytics as understood by the operators of a power plant means to provide interactive guidelines to advise the operator to take the right steps, and to provide a mechanism to learn from past incidents. Therefore a sensor-based ontology represents a predictive model for the behaviour of mechanical and electrical parts of a power plant under certain circumstances. Rules are crucial in this application, as they represent, as so called monitors, complex relationships between different elements (energy medium, parts of the plant, and environmental influence) and their behaviour in time. Acting as semantic agents, these monitors observe the power plant and create alerts in case of an incident. The alert is used by an ontology-based advisory system which guides the operator how to deal with and fix the problem. The knowledge engineer is able to improve the system by learning from past incidents by analyzing the stored incidents and derive new experience and monitors from. Monitoring systems may be classified as business analytics systems and thus this application shows the benefits of semantic technologies in business analytics respectively business intelligence.