Model-Based Systems Engineering with SysML v1

Description

Model-Based Systems Engineering (MBSE) with SysML v1 is a course intended for practicing systems engineers who want to learn how to apply model-driven engineering practices using the Systems Modeling Language™ (SysML® v1.6).

The course begins with an overview of MBSE and SysML and continues with the first step in the method which is to understand the problem to correctly frame the solution. Students are then introduced to requirements and use cases and how to model them in SysML. Packages are discussed to represent different strategies for organizing SysML models.
The course introduces sequence diagrams to represent message exchanges. Allocations are discussed for mapping behaviors to structural elements. Students are shown how state machines are used to capture event-based behaviors. Block definition diagrams (BDD) are used to show the constituent parts of a system and internal block diagrams (IBD) are used to show the connections between those parts.
The course finishes with an introduction to activity models for representing functional behavior and then the usage of parametric diagrams to capture inter-related sets of formulas (as constraints).

Course Outline (Modules and Topics)

Prerequisites

Participation in system engineering projects

Continuing education

Sparx EA System Engineering

Classroom requirements

None

Audience

Systems Architect I Systems Engineer I Systems Analyst
Test Engineer I Project Manager

Objectives

  • Productivity through Model-Based Systems Engineering Principles and Practices
  • Identify and describe use of all nine SysML v1 diagrams
  • Follow a formal methodology to produce a system model
  • Follow a formal methodology to produce a system model
  • Model system behavior
    • Activity diagram
    • State machine diagram
    • Sequence diagram
  • Model requirements using requirements diagrams
  • Model requirements using use case diagrams
  • Model structure using block diagrams
  • Allocate behavior to structure in a model
  • Recognize parametrics and constraints and describe their usage