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Advanced MBSE: Managing Models and Modelers (APPEL – vAMBSE1)

PARTICIPANT TESTIMONIALS

  • Systems Engineering & Engineering
    Systems Engineering & Engineering

Skill Level: Project Managers/Project Systems Engineers or higher.

This course provides a common foundation of knowledge and skills for NASA MBSE Modeling Leads, and is a prerequisite for other courses in this series. The course focuses on hierarchy and flow as crucial concepts for effective system and process design. We explain how these concepts effect our ability to translate stakeholder needs into requirements, describe the necessary behavior and structure of our system, manage risk, plan our test program, and maintain the system after deployment.

We will review the foundations of essential MBSE processes and methods. Then, we will build a sample model from “scratch,” using a robust process to analyze how MBSE methods can be incorporated across the system/process lifecycle. Our efforts will aid in the efficient and effective identification of opportunities to create consistency across projects and sites.

This highly interactive course presents a fresh view of the systems engineering process that delivers essential insights into the interconnectivity of diagrams and relationships, the origins of necessary information, and drives systems thinking throughout a system’s life. After this course, you will have practical experience deploying the fundamentals of MBSE/SysML in a sample project that simulates real-world scenarios we encounter on the job. You will recognize robust development processes as critical enablers to a successful MBSE effort. You will have the confidence to deploy MBSE/SysML on your projects in a manner that adds value and encourages robust systems thinking.

Topics include:

  • Overview/review of SysML syntax
  • Review of the purpose of each SysML diagram type
  • Concepts in process definition and modeling
  • MBSE as an enabler for effective development processes in NASA

Advanced MBSE Series: This course is a part of a series designed for systems engineers with advanced exposure to modeling processes. All courses within this series can be found in the Supplemental Resources tab under "Related Courses".

Required Prerequisite: foundational understanding of systems engineering principles and model-based systems engineering processes is necessary.

Recommended Sequence: to maximize conceptual understanding of advanced MBSE skills, courses within this series should be taken in sequential order.

Related Resource: NASA Advanced MBSE Course Alignment

This online course series is designed for:

  • individuals experienced with basic systems engineering methods, MBSE concepts, a basic understanding of the SysML language, and familiarity with the Cameo toolset.
  • Individuals who want more practical experience and confidence deploying MBSE on the job.
  • Individuals who will lead the MBSE effort for their projects and teams.
  • Individuals who need to understand and characterize the relationships among system behaviors and system structures.
  • Individuals who will deploy MBSE/SysML on their projects and across the organization.
Project Management Competencies
  • PM 2.0 – Stakeholder Management
  • PM 13.0 – Systems Engineering
Common Competencies
  • C 4.2 – Communication
Systems Engineering Competencies
  • SE 1.1 – Stakeholder Expectation Definition & Management
  • SE 1.3 – Logical Decomposition
  • SE 1.4 – Design Solution Definition
  • SE 3.1 – Technical Planning

Click here to view full competency model.

When you complete this course, you will be able to:

  • Build coherent, cohesive SysML models – from the ground up.
  • Recognize and understand the interconnections among SysML Diagrams.
  • Implement a robust, repeatable process for model generation that ensures all modeling efforts are approached with the same set of repeatable steps.
  • Discern when and how to implement SysML to enable robust processes.
  • Drive consistent, standard approaches to model organization, modeling strategy, and model building across projects.
  • Understand the information necessary – and its origins – to populate a well-formed model.