Formalizing “Model-Based System Engineering” (MBSE) through integration of best-of-breed tools, models, and data
- Oct 1, 2018
Model-based system engineering (MBSE) seeks to formalize the modeling required for analysis and simulation across the lifecycle (requirements, design, verification, validation, operations, and finally sustainment). The intent is to begin with the official description of requirements and expand this through conceptual design into final design, and beyond.
Unfortunately, without formalized integration of existing best-of-breed models and tools, this process becomes out-of-sync as the early design expands in detail. This is largely due to challenges in incorporating physics and other models within the evolving descriptive system model, which provides the desired validation but quickly becomes only a graphical documentation artifact.
The descriptive model should serve as a standard description of the structural and behavioral aspects of a system, serving as an injection point for additional physics models and digital artifacts supplying context for the necessary analysis and simulation of the system.
Not only should MBSE serve as a basis for early design and trade space exploration necessary for requirement formalism, it should also seek to provide a cohesive, digital surrogate possible for simulation. This allows the official, descriptive model to remain in-sync as the design matures, not simply orchestrating the building blocks.
In a previous webinar on this topic, I focused on the use of the MBSE descriptive design as the actual model for simulation by infusing physics constraints allowing for the following:
- Better formulated and described requirements through the use of a domain ontology
- Evaluate detailed operational trades as the design matures by running simulations based on the authoritative model
- Incorporate detailed behavioral considerations, such as sub-system interaction rules, system operational tactics, and policy/doctrinal considerations to the descriptive architecture model as control parameters for concept-of-operation exploration and operational utility
- Use of the integrated and illustrative architecture model as the “digital surrogate” for operational course-of-action assessment and additional capability for sustainment exploration