In the area of digital technologies, the focus is on vertical IT integration, which means that research focuses on end-to-end, bidirectional data integration in accordance with the automation pyramid. This includes the implementation of all interfaces to demonstrate digital production and end-to-end data integration from the ERP to the store floor and back. Taking Industrial Internet of Things (IIoT) approaches into account, the dissolution of traditional multi-level vertical integration towards cyber-physical systems (CPS) is also being investigated. In this area, our investigations focus on the question of which functions will be performed at which levels or by which services in the future. In the area of IIoT, our focus is on researching digital retrofitting as a way of establishing the IP capability of machines of different ages and technologies. Another focus is on the evaluation and use of data using Advacend Analytics, which includes machine learning (ML), for example.
Research interests:
- What operational and also strategic steps are necessary to enable networked production?
- What can the digitization of machines and plants achieve?
- What information is required and which sensors can be used for data acquisition through digital retrofitting?
- Which communication protocols and which components should the IoT infrastructure/data pipeline include?
- How can the collected data be used for process optimization through industrial machine learning?
- What are 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 visualizations of machine data using dashboards
- Process optimization through the use of collaborative robots for assembling processes
- Digitalization of waste management for greater sustainability
- Machine learning models for automated quality control
- Predictive avalanche detection for more safety in winter tourism
