By linking data processing systems to industrial tools, machine tools and production facilities as well as workpieces that are the outcome of production and service processes, huge amounts of data are generated in current industrial environments. Industrial data clouds provide a solution for storing and pooling this data and allow for accessibility among multiple stakeholders. Smart data approaches constitute the foundation for opening up new value creation potentials by introducing methods such as data analytics, data visualization and business intelligence.
By contextualizing data, which is per se non-descriptive, with additional domain information, smart data is generated. These data sets bear high potential for innovating new services since they are based on evidence from real-world settings.
However, the development of new services among machine manufacturers, logistics providers, mid-sized industrial service providers and start ups is compromised by the lack of simple and easy to handle service engineering approaches that make use of the potential from huge amounts of data. Hence, there is no guidance for innovating new services with multiple stakeholders in a systematic, evidence-based manner.
This gap is addressed by SmartDiF in terms of piloting the engineering of new services based on the infrastructure of industrial clouds as a prototypical development environment.