This includes implementing all interfaces to demonstrate digital production and end-to-end data integration, from ERP to the shopfloor and back. Following the Industrial Internet of Things (IIoT) approach, the disintegration of traditional 4-stage vertical integration is also examined. In this field our investigations are focused on determining which functions will in future be performed at which levels and by which services. Our research focus also lies on digital retrofitting as a potential means of ensuring the IP capability of machines of different ages and technologies.
Key research areas
- What operational and strategic steps are required to enable connected manufacturing?
- What impact can the digitalisation of machinery and plant have?
- What information is required, and which sensors can be used for data collection through digital retrofitting?
- Which communication protocols and components should the IoT infrastructure/data pipeline include?
- How can the collected data be used for process optimisation through industrial machine learning?
- What are the future trends in digital production and how can companies benefit from them?
Use cases
- Condition monitoring, energy monitoring and tool management of digitally retrofitted machines for transparent production
- Real-time visualisation of machine data via dashboards
- Process optimisation through the use of collaborative robots for assembly processes
- Digitalisation of waste management for greater sustainability
- Machine learning models for automated quality control
- Predictive avalanche detection for greater safety in winter tourism