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Visit outline: MBSE with Automation (Course code: mbsea)
Summary
Overview
This session is a technical course module focused on domain modeling in systems engineering, with an emphasis on leveraging AI (specifically ChatGPT) to accelerate the identification of system functions and promote consistency in terminology across project teams. The instructor demonstrates how to export and share a domain model diagram using Cameo, then transitions into discussing the value of aligning stakeholders on shared nouns before writing requirements or use cases. The session highlights an AI-assisted approach to object-oriented design—bypassing traditional activity diagram decomposition by using AI to generate operations and attributes for domain objects. The session concludes with a planned break before moving into the next module on AI-assisted requirements.
Topic (Timeline)
1. Domain Model Export and Sharing [00:00:03 - 00:02:10]
The instructor demonstrates exporting a domain model from Cameo using the “Save as Image” feature, attempting to transfer the image file to another participant’s virtual machine. Technical challenges arise around file permissions and cross-machine file transfer. The instructor considers alternatives, such as leaving the diagram visible on-screen or relying on slides, to avoid transfer complications. The session pauses while participants address unrelated tasks.
2. ChatGPT Account Setup Guidance [00:02:10 - 00:03:48]
The instructor advises participants to create a ChatGPT account via OpenAI.com or chatgpt.com to enable hands-on experimentation with AI prompting. One participant recalls having an existing account but struggles to locate the sign-up option, prompting a discussion about the proliferation of similar-looking websites. The instructor clarifies that while an account is not mandatory, it is recommended for active participation in AI-driven exercises.
3. Domain Modeling Best Practices and AI-Assisted Object Design [00:04:45 - 00:07:50]
The instructor emphasizes the importance of publishing the domain model early to ensure all team members use consistent terminology when writing requirements or use cases. The session introduces an AI-generated table that maps domain objects to their attributes (SysML value properties) and operations (functions), revealing that ChatGPT has implicitly performed object-oriented design by assigning operations to domain objects. The instructor notes that this approach bypasses traditional functional decomposition via activity diagrams, achieving a reasonable set of system functions more efficiently. The value of AI in accelerating design discovery is explicitly highlighted.
4. Lab Review and Break Announcement [00:07:50 - 00:16:23]
The instructor reviews the prior lab activity, inviting questions. No questions are raised. A 10-minute break is announced to allow Elena to complete her domain model diagram, with the next module on AI-assisted requirements scheduled to begin after the break. The instructor checks for understanding on domain modeling, expresses uncertainty about unintended content creation, and attempts to re-access a shared screen, ending the session on a note of transition.
Appendix
Key Principles
- Consistent Terminology: Use a published domain model to align all stakeholders on shared nouns for requirements, use cases, and design.
- AI as Design Accelerator: Leverage AI to auto-generate operations and attributes for domain objects, bypassing manual activity diagram decomposition.
- Object-Oriented Insight: AI naturally performs object-oriented design by associating functions (operations) with domain entities, even without explicit modeling.
Tools Used
- Cameo (for domain model export via “Save as Image”)
- ChatGPT / OpenAI (for generating attribute and operation tables from domain models)
- Web browser (for account creation and AI interaction)
Common Pitfalls
- Confusion over legitimate vs. phishing sites when accessing OpenAI/ChatGPT.
- File transfer limitations between virtual machines or user accounts.
- Over-reliance on manual functional decomposition (activity diagrams) when AI can provide rapid functional insights.
Practice Suggestions
- Export and share domain models early in the project lifecycle.
- Use AI to generate a table of domain objects, attributes, and operations as a starting point for logical architecture.
- Compare AI-generated functions against manually derived ones to validate completeness and identify gaps.