Data modelling in production engineering

 

Turning Data into Value - How does it work?

Assistant demonstrates data modeling on a screen © RWTH International Academy  

Production data only provide added value when they are put into a proper context. A measured value from the temperature sensor (36), for example, only becomes valuable information when the measuring point (guide rails of the WZM) and the unit used (Degree Celsius) are known. To contextualise production data, data models are used that are tailored to the respective application. The choice of modelling methodology depends in particular on the intended use of the data. Fast message exchange of a cell control, for example, does not require an elaborate data structure, whereas this may well be necessary for the construction of a digital shadow of the cell. Creating context-adequate, granular and, above all, reusable data models is one of the greatest challenges of today´s production technology. In Smart Automation Lab, the relevance of the topic does not go unnoticed: a large number of industry and research projects such as the Cluster of Excellence "Internet of Production" and iCellFactory deal with the problem of optimal, solution-bound data modelling.