Automated diagnosis of factories becomes increasingly important to avoid production stops and down times. Additionally, market trends such as small batch size induced by individual customer requirements lead to modular production systems elevating flexibility as well as complexity of smart factories. That leads to more difficulties using conventional diagnosis methods. The ever changing constellations of production modules requires to include context information of the manufacturing domain to enable a suitable fault diagnosis.This paper shows the identification and classification of relevant context information for fault diagnosis in skill-based production systems. The concept of faults is embedded into the Capability-Skill-Service Model used to describe the aforementioned context. Suitable entities and their relations in the production system are outlined and the Knowledge Graph technology is used to make the the context information accessible. An implementation in a real-world demonstrator of SmartFactory-KL is presented and an outlook for further research is given.

To improve the fault tolerance of production systems against unforeseen events, modern production systems must be able to react more autonomously with suitable solutions to reach their goals. Such events within the company, e.g., resource breakdowns, require the possibility of internal replanning of the production schedule. Multi-Agent Systems (MAS) can provide this required flexibility. To enable standardized interaction for agents, a vendor-independent description of products and production equipment, as well as their capabilities and skills, must be developed. The Asset Administration Shell (AAS) provides the standardized meta-model to achieve this goal. In this paper, a product AAS and the submodel for the required production plan are designed. Moreover, the associated MAS and interaction for the execution and replanning of the production sequence are presented. The system is validated using an assembly use-case in the real-world demonstrator environment of the SmartFactoryKL. Combining the concepts of MAS with the standardized structures of the AAS, skills and capabilities tackles the problem of MAS to be deployed in different companies. This approach enables widespread use and scalability of MAS leveraging their advantages in terms of flexibility and efficient reconfiguration.

Functionally described capabilities play an important role in the virtualization of manufacturing and the resource-specific realization with the skill-based approach. The importance of this modeling can be seen in a formalization of production capabilities for a holistic usage in a workflow from product orders towards manufacturing on the shop floor. This paper presents a concept for modeling and usage of functionally described capabilities along this workflow with combined modeling approaches. Therefore, the formalism and the setup of product requirements, functionally described capabilities, Petri Net Plans for creation of resource-specific process sequences, and at least their execution with skills are considered. The application and validation of this concept on a virtualized demonstrator example is shown. The achieved results for a given application from a product order towards its simulated manufacturing are presented.