Defining a Context Model for Smart Manufacturing

In smart manufacturing, automatically detecting and controlling a situation becomes more and more important. During a production, a variety of machine errors and failures may occur. In order to take further measures and decisions, context information is important to understand the situation and to identify the need for action. Context information enables decisions and allows processes to adapt as precisely as possible. The development of a suitable context model for smart manufacturing is a very complex task. In this paper, we describe an approach for the development of a semantic context model and present use cases that show, how context information can be used for smart manufacturing. In an ongoing research project about self-adaptive production processes, we categorized context information based on selected use cases and complemented the results in an entity model. We implemented this context model for a lab-based smart manufacturing prototype, using a context data storage and an annotation component. For the context model, different submodels, such as the entity and instance model, have been developed. In the implementation, the context model is the basis for flexible and self-healing processes, which will be evaluated in use cases. The result of our context modeling process is an OWL context model for smart manufacturing.