Cyber-physical systems (CPSs) combine software and hardware components to form complex, intelligent, integrated entities. Autonomous robots, production lines, and even complete infrastructure systems such as power grids or transport networks are all examples of CPSs. They are a basic element of industry 4.0 and are expected to make major contributions to the modularisation, flexibilisation, and adaptability of industrial production processes.
CPSs may be viewed as a further development of the mechatronic systems that are deployed today. However, they have far more powerful software, which is built on, among other things, self-learning algorithms like machine learning or artificial intelligence. CPSs' connectivity is not limited to a single site. They can be interconnected globally with other CPSs or networks. The complex interactions between the individual components make it significantly more difficult to assess the safety of these systems.
The safety aspects of such systems can no longer be described adequately by the risk analysis methods common in industrial practice today, e.g. failure mode and effects analysis (FMEA) or fault tree analysis (FTA). Recently developed statistical risk analysis methods may possibly be better suited for the assessment of CPSs.
A concrete application scenario that can serve as a reference point is required in order to review the new methods' effectiveness in practice, and explore their capabilities and limitations. This project will therefore investigate a modular, adaptable, networked production line and assess it using various quantitative risk analysis procedures. The first step will be to construct a digital system model. The second step will involve testing new risk analysis methods on this model and expanding or modifying them as necessary.
The findings arrived at are to inform practical recommendations concerning risk analysis that can subsequently be drawn on for standardisation activities and other purposes. Furthermore, it is hoped the digital system model and its risk analysis can be used to identify potential approaches to the improvement of system safety. The project's results will therefore contribute to the appropriate assessment of employees' safety in emerging industry 4.0 scenarios.
Unit 2.4 "Workplaces, Safety of Machinery, Operational Safety"