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Duration 21 hours (3 days)
Course Outline
Three-Day Training Agenda
Day One
Overview of the AIM Process
- Definition and scope of the AIM Process.
- Critical dependence of system functionality on software components.
- Strategic roadmap for concurrent hardware and software design.
AI Integration in Model-Based Systems Engineering (MBSE)
- Methods for leveraging AI to enhance MBSE workflows.
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Development of AI Personas and Autonomous Agents
- Utilizing AI as a domain subject matter expert.
- Employing AI as a design support tool.
- Applying AI for code synthesis.
- Best practices for effective prompt engineering.
Case Study: Scanning Electron Microscope (SEM)
- Presentation of the SEM reference architecture.
- Application of AIM principles to SEM systems.
Foundations of SysML and Introduction to SysML v2
- Comprehensive overview of SysML standards.
- Core elements and diagram types within SysML.
- Overview of SysML v2 enhancements and operational benefits.
Domain Modeling
- Strategic importance of domain modeling in governance.
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Practical Laboratory Session: Domain Modeling
- Participants utilize AI to construct a Domain Model for the SEM.
Requirements Engineering
- Techniques for drafting precise and actionable requirements.
- Leveraging AI to optimize requirements elicitation.
- Application of Zigzag Prompting techniques.
- Implementation of Deep Dive Prompting strategies.
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Practical Laboratory Session: Requirements Modeling
- Participants utilize AI to capture and formalize SEM requirements.
Use Case Definition
- Role of use cases in MBSE frameworks.
- Authoring robust and effective use case documentation.
- AI-assisted creation of use cases, emphasizing alternate and exception flows.
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Automated Executable Wireframes
- Generation and validation of wireframe interfaces.
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Practical Laboratory Session: Use Cases
- Participants utilize AI to draft use cases and produce wireframes for the SEM.
Day Two
Logical Architecture
- Summary of Logical Architecture concepts.
- Interdependencies among key components.
Domain-Driven Logical Architecture
- Decomposition of subsystems.
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Object-Oriented Methodology in MBSE
- Advantages of adopting an object-oriented paradigm.
- Comparative analysis with conventional engineering methods.
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Mitigation of Item Flow Violations
- Protocols for preventing flow violations.
- Identification and avoidance of common architectural errors.
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Construction of Logical Models
- Applied exercises in logical model development.
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Practical Laboratory Session: Logical Architecture
- Participants utilize AI to establish a Logical Architecture for the SEM.
Physical Architecture and Parametric Analysis
Physical Architecture
- Component configuration and relational mapping.
- AI-assisted component identification.
- Conducting trade study analyses.
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Practical Laboratory Session: Physical Architecture
- Participants utilize AI to define a Physical Architecture for the SEM.
Foundations of Parametric Modeling
- Integration of parametrics into MBSE practices.
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Development of Parametric Models
- Applied exercises in parametric modeling.
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Practical Laboratory Session: Parametrics
- Participants utilize AI to construct Parametric Models for the SEM.
Day Three
Software Engineering Integration
Microcontroller Code Synthesis
- AI-driven code generation for embedded microcontrollers.
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Practical Laboratory Session: Microcontroller Code Generation
- Participants utilize AI to synthesize microcontroller code for the SEM.
Database Code Synthesis
- AI-driven code generation for database structures.
- Overview of MongoDB and the MERN technology stack.
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Practical Laboratory Session: Database Code Generation
- Participants utilize AI to generate database logic for the SEM.
User Interface Code Synthesis
- AI-driven code generation for frontend interfaces.
- Introduction to React JS framework.
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Practical Laboratory Session: User Interface Code Generation
- Participants utilize AI to develop user interface code for the SEM.
Verification, Validation, and SysML v2
Testing within MBSE
- Best practices for comprehensive testing strategies.
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Practical Laboratory Session: Testing
- Participants utilize AI to formulate test cases for the SEM.
Creation of SysML v2 Models
- Detailed introduction to SysML v2 standards.
- Operational benefits and new functional capabilities.
- Illustrative examples and applied exercises.
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Guided Session: Generating SysML v2 Models
- Supervised exercise in SysML v2 model generation.
Requirements
- Foundational knowledge of Model-Based Systems Engineering (MBSE) and SysML is recommended.
- Prior experience with modeling tools such as Cameo Systems Modeler or Sparx Enterprise Architect is advantageous.
- Programming experience is not mandatory; however, familiarity with microcontrollers, database architectures, and user interface concepts is beneficial.
- Basic proficiency with AI-driven products, such as ChatGPT, is recommended.
- None of the aforementioned items are strict prerequisites for enrollment.
Target Audience
- Systems Engineers.
- Software Engineers.
- Managers overseeing System and Software Engineering functions.
Testimonials (1)
This class presents material that will be disruptive to industry. Those who do not adopt will miss out.
