BPMN for knowledge acquisition and anomaly handling in CPS for smart factories

Abstract

In this paper, we describe a real-time knowledge acquisition and anomaly handling architecture in a maintenance scenario of an industrial cyber-physical production environment. We use the Business Process Model and Notation (BPMN) for modeling and controlling of the maintenance procedure. Automatic handwriting and pen gesture recognition is combined with a networked smart pen that is used on semantically structured paper forms. Here, we discuss our architecture with BPMN-modeled workflows for real-time data processing. All detected anomalies are automatically associated to the corresponding knowledge sources such as the process model, structure model, business process model and user models; linked Semantic Media-Wiki (SMW) pages are built up accordingly. Our architecture provides for a seamless integration of real-time knowledge sources by smart pen technology and real-time CPS processing by a BPMN engine handling the execution and coordination of the modeled interactions.