Fraunhofer Institute for Production Systems and Design Technology
MBSE for Companies
In many companies, the system structure is given by the product structure in the PDM, but does not contain interface descriptions between system elements.
MBSE enables end-to-end system modeling with open interfaces for system development. The concept of the digital twin uses models beyond development and validation also for operational optimization. Especially to reduce the effort of developing digital twins, it is necessary to think about the different elements already during system development and integration. Model-based systems engineering as a system development concept is particularly suitable for providing significant support for the digital master, but also for the digital shadow and the linking of these two elements. In the context of MBSE, the two dimensions of digital twins "Digital Model Richness" and "Simulation Capabilities" can benefit from synergies by carrying the concept of data continuity with MBSE beyond system development into the entire downstream lifecycle. This allows Digital Twins to be developed and operated more efficiently. MBSE development capabilities can be divided into five basic aspects:
- Systems Environment Analytics
- System Definition und Derivation
- Systems Interaction Modeling
- Systems Lifecycle Engineering
- MBSE Capability Maturation Matrix
These five MBSE disciplines provide process- and method-independent development skills needed for model-based development of complex systems and can be used for more efficient development of digital twins.
MBSE development capabilities for the use of digital twins and co-simulations.
| MBSE discipline | Systems Environment Analytics | System Definition und Derivation | Systems Interaction Modeling | Systems Lifecycle Engineering | MBSE Capability and Maturation Matrix |
| MBSE development capability | Identifying interacting systems and describing the types of interactions | Generating models that represent systems from different points of view | Modeling and simulation of the behavior of the system under consideration | Management and integration of system models in the product life cycle | Acquiring and mastering the necessary MBSE competencies |
| Skills for the Digital Master | Semantic linking of partial models | Complete modeling of all system elements | Dynamic recording and management of time-dependent data | Integration of configuration parameters and management of versions | Assessment of the requirements for the Digital Master |
| Capabilities for the Digital Shadow | Assessment of the necessary input variables/ data basis, completeness check | Easier assignment to architectural elements of the system becomes easier | More efficient use of the data basis, due to only linearly independent input variables, model quality can be determined | Management of access rights to data | Reuse of the Digital Twin |