Course Code: ai4mbse
Duration: 21 hours
Prerequisites:
  • Some basic understanding of Model Based Systems Engineering and SysML is desirable
  • Experience with tools like Cameo Systems Modeler or Sparx Enterprise Architect is desirable
  • No programming experience irequired but familarity with microcontrollers, databases, and UI is helpful
  • Familiarity with AI products such as chatGPT is helpful
  • None of the above are absolute prerequisites

Audience

  • Systems Engineers
  • Software Engineers
  • System and Software Engineering Managers
Overview:

This instructor-led, live training (online or onsite) is aimed at professionals who wish to use AI to accelerate their systems and software engineering work.  If you've been wondering how to use AI to dramatically accelerate your systems engineering work, this class is for you. 

Students will model a Scanning Electron Microscope (both hardware and software) as their lab exercise, learning how to ask the right questions (i.e. prompts) to get help from AI in constructing the model.

By the end of this 3-day class, participants:

  •  will learn how to use AI as a "subject matter expert" in defining the system/software model. 
  •  will be familiar with "the four pillars of SysML" (Requirements, Structure, Behavior and Parametrics)
  •  will also know how to structure their SysML models to account for software, 
    • generate User Interface Code from Behavior Models, 
    • generate Database Code from Structure Models, 
    • generate Microcontroller Code from State Machines

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
Course Outline:

3 DAY COURSE AGENDA

Day One

Introduction to AIM Process

  • What is AIM Process?
  • "Without software, there is no system"
  • A Process Roadmap for Hardware/Software Co-Design

AI Acceleration in MBSE

  • How AI accelerates MBSE
  • Developing AI Personas and Agents
    • AI as a subject matter expert
    • AI as a design assistant
    • AI as a code generator
    • Effective prompting strategies

Scanning Electron Microscope Example

  • Introduction to the SEM example
  • Relevance and application of AIM in SEM

SysML Basics and Introduction to SysML v2

  • Overview of SysML
  • Key elements and diagrams in SysML
  • Introduction to SysML v2: benefits and new features

Domain Modeling

  • Importance of domain modeling
  • Hands-on Lab Session: Domain Modeling
    • Students use AI to help create a Domain Model for the SEM

Requirements Engineering

  • Writing clear requirements
  • Using AI to enhance requirements gathering
  • Zigzag Prompting
  • Deep Dive Prompting
  • Hands-on Lab Session: Requirements Modeling
    • Students use AI to help gather and write requirements for the SEM

Use Cases

  • Importance of use cases in MBSE
  • Writing effective use cases
  • AI for writing use cases, focusing on alternate and exception behavior
  • Automated Executable Wireframes
    • Creating and validating wireframes
  • Hands-on Lab Session: Use Cases
    • Students use AI to help write use cases and create wireframes for the SEM

Day Two

Logical Architecture

  • Overview of Logical Architecture
  • Key components and their relationships

Domain-Driven Logical Architecture

  • Subsystem decomposition
  • Object-Oriented Approach in MBSE
    • Benefits of an object-oriented approach
    • Comparing with traditional methods
  • Avoiding Item Flow Violations
    • Strategies to prevent item flow violations
    • Common pitfalls and how to avoid them
  • Developing Logical Models
    • Hands-on exercises with logical models
  • Hands-on Lab Session: Logical Architecture
    • Students use AI to develop a Logical Architecture for the SEM

Physical Architecture and Parametrics

Physical Architecture

  • Key components and their relationships
  • Using AI to identify components
  • Trade studies
  • Hands-on Lab Session: Physical Architecture
    • Students use AI to develop a Physical Architecture for the SEM

Introduction to Parametrics

  • How parametrics enhance MBSE
  • Developing Parametric Models
    • Hands-on exercises with parametric models
  • Hands-on Lab Session: Parametrics
    • Students use AI to develop Parametric Models for the SEM

Day Three

Software Development

Microcontroller Code Generation

  • AI-driven code generation for microcontrollers
  • Hands-on Lab Session: Microcontroller Code Generation
    • Students use AI to generate microcontroller code for the SEM

Database Code Generation

  • AI-driven code generation for databases
  • Introduction to MongoDB and MERN Stack
  • Hands-on Lab Session: Database Code Generation
    • Students use AI to generate database code for the SEM

User Interface Code Generation

  • AI-driven code generation for user interfaces
  • Introduction to React JS
  • Hands-on Lab Session: User Interface Code Generation
    • Students use AI to generate user interface code for the SEM

Testing and SysML v2

Testing in MBSE

  • Strategies for effective testing
  • Hands-on Lab Session: Testing
    • Students use AI to develop test cases for the SEM

Generating SysML v2 Models

  • Introduction to SysML v2
  • Benefits and new features
  • Practical examples and exercises
  • Hands-on Session: Generating SysML v2 Models
    • Guided exercise on generating SysML v2 models
Sites Published:

USA - AI Assisted MBSE with SysML

Uzbekistan - AI Assisted MBSE with SysML