Cyber-physical production systems and digitalization of the value chain in scope of “Industrie 4.0“ create data volumes that can now be analyzed with BigData and SmartData technologies. This creates new opportunities to raise predictive information e.g. about optimal maintenance schedules and enables improved service performance.
To comprehensively perceive the benefits of predictive maintenance in services and archive economically optimal use, the value chain of industrial services must be considered as a whole. This is especially interesting, as such services are time and cost intensive and new business models with flat fees (“full service“) are increasingly in demand. STEP is concerned with cost efficient and ideal economic planning of such maintenance services.
Based on a to be created vision of industrial services and maintenance in the age of industrie 4.0 new business models, required methods and information demand will be derived, which leads to an economical optimal service plan. STEP will develop technologies, which support innovative planning practices and the provision of assignment related information for the service technician of the future.
Project participants: USU Software AG (Konsortialführer), FLS GmbH, Heidelberger Druckmaschinen Aktiengesellschaft, Karlsruher Institut für Technologie (KIT), TRUMPF Werkzeugmaschinen GmbH + Co. KG