Model Based System Engineering
Model-based systems engineering (MBSE) is a formalized methodology that is used to support the requirements, design, analysis, verification, and validation associated with the development of complex systems. In contrast to document-centric engineering, MBSE puts models at the center of system design. *
More about MBSE
MBSE in a digital-modeling environment provides advantages that document-based systems engineering cannot provide. For example, in a document-based approach, many documents are generated by different authors to capture the system's design from various stakeholder views, such as system behavior, software, hardware, safety, security, or other disciplines. Using a digital-modeling approach, a single source of truth for the system is built in which discipline-specific views of the system are created using the same model elements. *
A digital-modeling environment also creates a common standards-based approach to documenting the system that can be programmatically validated to remove inconsistencies within the models and enforce the use of a standard by all stakeholders. This common modeling environment improves the analysis of the system and reduces the number of defects that are commonly injected in a traditional document-based approach. The availability of digitalized system data for analysis across disciplines provides consistent propagation of corrections and incorporation of new information and design decisions (i.e., state it once and automatically propagate to various views of the data) to all stakeholders. When MBSE is done properly, the result is an overall reduction of development risks. *
MBSE brings together three concepts: model, systems thinking, and systems engineering: *
A model is a simplified version of something--a graphical, mathematical, or physical representation that abstracts reality to eliminate some complexity. This definition implies formality or rules in simplifying, representing, or abstracting. To model a system, a systems architect must represent the system with less detail so that its structure and behavior are apparent and its complexity is manageable. In other words, models should sufficiently represent the system, and the system should confirm the models. *
Systems thinking is a way of looking at a system under consideration not as a self-sufficient entity, but as part of a larger system. Systems thinking is not the same as a systematic adherence to following good plans, collecting statistics, or being methodical. The systems engineer observes the system from a distance; explores its boundaries, context, and lifecycle; notes its behavior; and identifies patterns. This method can help the engineer to identify issues (e.g., missing interaction, a missing step in a process, duplication of effort, missed opportunity for automation) and manage a system's complexity. Although systems engineers must break down and analyze the system in the beginning--identify parts and describe connections between them--with systems thinking, they later synthesize the parts back into a coherent whole. Parts are not just connected to other parts, they depend on each other to work properly. Systems thinking emphasizes this interconnectedness. The behavior of the system emerges from the activities of the system's subparts. Observing the system's interconnections, the systems engineer identifies feedback loops and causality patterns that may not be apparent at first. Systems thinking can help make issues more apparent and easier to identify, balance the system, and manage the system's complexity. *
Systems engineering is a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods. It brings together a number of techniques to make sure that all requirements are satisfied by the designed system. It concentrates on architecture, implementation, integration, analysis, and management of a system during its lifecycle. It also considers software, hardware, personnel, processes, and procedural aspects of the system. *
Shevchenko, N., 2020. *
* All information is derived from the following article, found at the link below. Click the link for additional information.
Shevchenko, N., 2020: An Introduction to Model-Based Systems Engineering (MBSE). Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed January 31, 2023, http://insights.sei.cmu.edu/blog/introduction-model-based-systems-engineering-mbse/.