Real MBSE: Functional Analysis and Simulation Without Pain Webinar

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Functional analysis is often considered the heart of systems engineering, a critical step that helps define exactly what a system needs to do to meet mission objectives. In the third part of our "Real MBSE" webinar series, Dr. Steven Dam demystified this process, demonstrating how modern tools like Innoslate enable efficient functional analysis and powerful simulation, transforming what can often be a painful process into a streamlined path toward mission success.

Why Functional Analysis Is Still King

While object-oriented analysis (OOA) has its place, particularly in software development, a functional approach remains essential for systems engineering. Systems engineers must focus on mission and system-level analysis and, crucially, behavior analysis. The core question is always: "Functionally, what am I doing? And not how am I doing it necessarily, but what am I doing?"

The key takeaway is that neither OOA alone nor functional analysis alone is sufficient for comprehensive systems engineering and program management. Lifecycle Modeling Language (LML), the foundation of the techniques discussed, is a hybrid language that integrates both object-oriented and functional analysis elements. This hybrid approach enables broader representation of systems engineering and the integration of program management disciplines, an area of increasing focus for organizations such as INCOSE and PMI.

The Critical Role of Simulation

Modeling and drawing diagrams are important, but they are not enough. Dr. Dam reminds us, "all models are wrong" until they are validated and tested. This is where simulation steps in.

Simulation is crucial for:

• Risk Analysis: Monte Carlo analysis is recommended to understand the range of potential outcomes and risks inherent in the system design.

• Calibrated Models: The ultimate goal of digital engineering is to create a well-calibrated model, a predictive analysis tool built upon experimental data. This allows engineers to narrow the range of uncertainty and make more precise predictions.

• Deriving Performance Requirements: Functional analysis provides the functional requirements (what the system does), while model simulation helps derive the performance requirements (how well the system must perform).

The Functional Analysis Process

Dr. Dam outlined a robust, multi-step process for functional analysis that transforms abstract user needs into concrete, verifiable system requirements:

1. Start with the Context Diagram: Define the problem's scope and identify external influences on the system or mission.
2. Create Scenarios (Use Cases/User Stories): These scenarios determine the types of missions the system must perform to meet user needs. A comprehensive set of scenarios is necessary to extract and derive the overall functional requirements.
3. Behavioral Modeling and Analysis: The scenarios are analyzed and modeled functionally (e.g., using Action Diagrams in Innoslate) to ensure behavioral consistency and performance.
4. Risk Mitigation: Incorporate risk analysis early. This includes identifying failure modes, contingency operations, and analyzing factors like availability, maintainability, reliability, safety, and security.

This process is highly effective both for systems being built from scratch and for analyzing existing, incomplete, or "sterile" sets of requirements handed down from other groups.

The CONOPS: Communicating the Vision

A vital artifact in this process is the Concept of Operations (CONOPS). More than just an operational concept diagram, the CONOPS is the primary tool for visualizing and articulating stakeholder expectations and requirements.

Scenarios are the heart of the CONOPS. By simulating these scenarios, engineers can quickly identify potential failures or timing conflicts in the proposed operational processes.

Conclusion

Functional analysis, when applied correctly with simulation, is the engine that drives robust, predictable, and successful system development. By adopting hybrid modeling approaches and leveraging tools that enforce behavioral consistency, systems engineers can eliminate the "pain" and deliver designs that truly meet the mission need.