Length: 3 Days
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Digital Engineering Fundamentals for Government Engineers

Digital Engineering Fundamentals for Government Engineers is a 3-day broad survey training program to provide the fundamental concepts of Digital Engineering (DEng) method to be delivered virtually.

Digital engineering can adapt your systems at the speed of relevance with automated system model and error reduction. Traditional systems engineering process can be likened to the telephone game with disconnected efforts.

Digital engineering is the art of creating, capturing, and integrating data using a digital skillset. From analysis to modeling and simulations, engineers will learn how to use advanced technologies to capture data and design in a digitized environment. Through progressive applications, the art of digital engineering enables designers to explore possibilities and develop innovative solutions in a virtual environment.

While models are considered as the most comprehensible form of digital engineering, it is the commutable data behind the model that opens the window to vast possibilities and opportunities.

Engineers will learn how to incorporate the use of digital computing, analytical capabilities, and new technologies to conduct engineering in more integrated virtual environments to increase customer and vendor engagement, improve threat response timelines, foster infusion of technology, reduce cost of documentation, and impact sustainment affordability.

These comprehensive engineering environments will allow agencies and its industry partners to evolve designs at the conceptual phase, reducing the need for expensive mock-ups, premature design lock, and physical testing.

Model-Based Systems Engineering (MBSE) is the practice of developing a set of related system models that help define, design, analyze, and document the system under development.

These models provide an efficient way to virtually prototype, explore, and communicate system aspects, while significantly reducing or eliminating dependence on traditional documents. MBSE is the application of modeling systems as a cost-effective way to explore and document system characteristics.

By testing and validating system characteristics early, models facilitate timely learning of properties and behaviors, enabling fast feedback on requirements and design decisions.

Historically, system decisions for requirements, designs, tests, interfaces, allocations, and others are maintained in a variety of sources, including documents, spreadsheets, domain-specific tools, and sometimes even on paper.

The MBSE approach is a holistic one key to Digital Engineering (DEng) to manage system information and data relationships, treating all information as a model.

An economic analysis demonstrates that there is a significant advantage to project performance by applying a model-based systems engineering (MBSE) approach.

An MBSE approach makes the engineering processes on a complex system development effort more efficient by improving requirements completeness, consistency and communication. These are seen in engineering processes involved in requirements management, concept exploration, design reuse, test and qualification, Verification and Validation, and margins analyses.

An MBSE approach has been proven to be most effective at improving defect prevention strategies. The approach is found to enhance the capability to find defects early in the system development life cycle (SDLC), when they could be fixed with less impact and prevented rework in later phases, thus mitigating risks to cost, schedule and mission.

Why Do You Need Digital Engineering and MBSE?

  • MBSE enhances the ability to understand, evaluate, communicate, and manage the data associated with the complete definition and specification of a product.
  • Improved communication among the stakeholders.
  • Enhanced ability to manage the system complication by modeling the system to be viewed from different points, and to analyze the impact of changes.
  • Higher quality by delivering a sharp and precise model of the system that can be evaluated for coherency, properness and wholeness.
  • Enhanced methods of gathering and re-using information by getting information in more organized approaches and empowering built-in concept mechanisms inherent in model driven approaches.
  • Improved ability to train the systems engineering fundamentals by demonstrating a sharp vision of the ideas behind.
  • The training programs helps to identify and maintain model-centric technology, model-based systems engineering (MBSE), high level knowledge of SysML and modeling notation, methodology/approach and usage preferably in a digital format (e.g., a digital system model(s)), that integrates the authoritative technical data and associated artifacts generated by all stakeholders throughout the system life cycle.
  • Digital system model(s) shall use standard model representations, methods, and underlying data structures. The digital system model(s) shall be a collaborative product of systems engineering and design engineering efforts. The program shall construct the digital system model(s) by integrating data consumed and produced by the activities across and related to the program. The digital system model(s) shall include technical baseline, parametric descriptions, behavior definitions, internal and external interfaces, form, structure, and cost. This data should be traced at a minimum from operational capabilities through requirements, design constructs, test, training, and sustainment. The program shall validate the digital system model(s) baseline at appropriate technical milestones.
  • Systems engineers shall use models to define, understand, evaluate, communicate, and indicate the project scope, and to maintain an “authoritative source” about the system. When captured digitally, the system model might be used to produce technical documentation and other artifacts to support program decisions. It is expected that a managed digitally based system model will be more accurate, consistent, and sharable.
  • Models, simulations, tools, methodology, and data employed in acquisition activities should have an established level of trust, and the program should use the activities with an acknowledged level of risk appropriate to the application.

Target Audience(s)

Government Engineers responsible for developing technical data, packaging technical data for leader’s decisions, and implementing technical processes within the systems development lifecycle. Participants will have significant engineering experience, but potentially limited exposure to DEng concepts.

Participants will learn how to use a digital model to develop depictions of the system to support all program uses, including ConOps, requirements analysis, architecture, design, test and evaluation, verification and validation, and cost trades; design evaluations; optimizations; system, subsystem, component, and sub-component definition and integration; cost estimations; training aids and devices development; developmental and operational tests; sustainment and disposal. In addition, models and simulations should be used, to the greatest extent feasible, in systems engineering and program/project risk management; cost and schedule planning; and providing critical capabilities to effectively address issues in areas including interoperability, collaboration, and systems of systems across the entire acquisition life cycle

These models would have to be connected to the physics-based models used by other engineering disciplines such as mechanical and electrical engineering. One challenge remaining for digital engineering is the integration of MBSE with physics-based models.

Learning Objective

To expose and level-set participants to important DEng concepts including optimization using digital models and software; model-based systems engineering, modeling notations and languages, SysML, visualizations; virtualization and simulation of design; management of assets; communication of complex engineering principles to stakeholders; and integration of data and information throughout the product lifecycle.

Participants will learn how to formalize the development, integration and use of models to inform enterprise and program decision making.

The following are some desirable characteristics of MBSE approaches:

  • Emphasizes a precise and complete System Architecture Model “blueprint,” typically organized using an Architecture Framework with multiple Views/Viewpoints, as the primary work artifact throughout the System Development Life Cycle (SDLC).
  • Promote the use of open standards for architectural modeling and tool interoperability(e.g., SysML, UML 2, XMI, AP233), where these open standards are used to specify the System Architecture Model and to serve as a lingua franca among Systems Engineers and other stakeholders (Software Engineers, Electrical Engineers, Mechanical Engineers, Customers, etc.).
  • Ensures that the System Architecture Model is architecture-centric to the extent that all model elements must maintain structural and functional integrity relationships and support full derivation traceability across all system stakeholder Views and Viewpoints.
  • Combine traditional Systems Engineering best practices with architecture modeling best practices.

Upon Completion of Digital Engineering (DEng) training, the participants can:

  • Describe principles behind Digital Engineering and Model-Based Systems Engineering (MBSE)
  • Articulate the benefits and challenges of Digital Engineering (DEng) and Model-Based Systems Engineering.
  • Develop a comprehensive knowledge of the key aspects of Digital Engineering (DEng)
  • Learn how to use digital engineering to build complex systems, the analysis of complex system of systems (SoS), model management and simulation
  • Describe how MBSE supports systems engineering processes
  • Recognize the various types of MBSE methodologies
  • Apply MBSE knowledge in your day-to-day SE work
  • Learn the basic principles of requirements, architecture, low level design models
  • Learn the basic principles of verifying and validating models
  • Apply Digital Engineering (DEng) to create systems architecture as a series of decisions
  • Learn what SysML is
  • Learn about SysML diagrams
  • Learn the benefits of implementing MBSE and SysML in a modeling environment and tools
  • Learn SysML fundamental constructs
  • Describe how SysML fits with related MBE/MBSE technologies
  • Discover the benefits of a SysML-based MBE/MBSE approach
  • Create a plan to deploy Digital Engineering (DEng), MBSE and SysML technologies in your organization

Training Outline

Digital Engineering Principles

  • Digital Engineering (DEng) Transformation
  • Digital Engineering Process, Methods and Tools
  • Transforming systems engineering through Digital Engineering (DEng)
  • Principles Behind Systems Engineering
  • Model-Based Systems Engineering (MBSE)
  • Digital Engineering (DEng) and Relationship with MBSE
  • MBSE and the s=Systems Engineering Activities
  • Modeling Requirements, Architecture, Design, Verification, and Validation

Model-based Systems Engineering (MBSE) Applied to Digital Engineering (DEng)

  • Definition of Model-Based Systems Engineering (MBSE)
  • System Model
  • Contrasting Document-Based SE with MBSE
  • Purpose for Modeling a System
  • Requirements for a system engineering process
  • What is a model?
  • An Integrating framework for the Systems Engineering
  • MBSE definitions
  • MBSE benefits and advantages
  • Unlocking the power of MBSE
  • Requirements
  • Behavior
  • Communication
  • Four elements of a model
  • Characteristics of a model
  • System modeling language
  • Modeling the  behavior
  • Structure and system relationships
  • the model  and concept of the design
  • MBSE Methodologies
  • MBSE  model and system definition language
  • Modeling languages and information standards
  • UML
  • SysML

MBSE Across the System Life Cycle

  • MBSE ‘s role to facilitate traditional SE activities
  • Specification and design precision
  • System design integration
  • Re-use of system artifacts
  • Output of MBSE as a system model
  • Model Requirements
  • Model Analysis and Design
  • Model Simulation
  • Model Code
  • Model Test
  • Simple Model Construction
  • Requirements, functions, and components
  • Modeling Notations
  • Integrated graphical views
  • Hierarchies
  • Functional flow and enhanced functional flows
  • N2
  • IDEF0
  • Physical block
  • Systems Engineering Solutions
  • Robust and agile analysis
  • Requirements definition through architecture to systems verification
  • End-to-end traceability
  • Extensive behavioral modeling representing control flow, function flow, and interface flow
  • System simulations
  • Behavioral models
  • Integrated Model-Based
  • Model Based Operational  and System Architecture
  • Languages, Processes, Tools and architecture frameworks

Overview of SysML

  • Introduction to the OMG Systems Modeling Language (OMG SysML™)
  • 4 Pillars of SysML
  • SysML Diagram Types
  • SysML Diagrams
  • Package diagram
  • Requirement diagram
  • Use Case diagram
  • Block Definition diagram
  • Internal Block diagram
  • Activity diagram
  • Sequence diagram
  • State Machine diagram
  • Parametric diagram

Modeling with SysML

  • Using SysML in Support of MBSE
  • Modeling Functionality with Use Cases
  • Modeling Requirements and their Relationships
  • Modeling Structure with Blocks (Block Definition Diagrams)
  • Modeling Structure with Blocks (Internal Block Diagrams)
  • Modeling Flow-Based Behavior with Activities
  • Modeling Event-Based Behavior with State Machines
  • Modeling Message-Based Behavior with Interactions
  • Modeling Constraints with Parametrics
  • Modeling Cross-Cutting Relationships with Allocations

Working with MBSE Domains

  • Architecting, specifying and developing complex systems
  • Process Domain (SE activities)
  • Source Requirements Domain
  • Behavior Domain
  • V&V Domain
  • Architecture Domain

Digital Engineering (DEng) and MBSE Gears

  • Functional currents and improved functional flows
  • N2
  • IDEF0
  • Physical block
  • Systems Engineering Solutions
  • Robust and agile analysis
  • Requirements definition
  • Systems verification
  • End-to-end monitoring
  • Broad behavioral modeling illustrating control flow, function flow and interface flow
  • System simulations
  • Performance models
  • Combined Model-Based
  • Model Based operational and system architecture

Digital Engineering Best Practices

  • Modeling and Simulation (M&S)
  • Model-Based Test and Evaluation (T&E)
  • Model-Based Requirements Engineering
  • 3D Design
  • Virtual Reality Simulation
  • Augmented Reality

Workshops: Working with Digital Engineering (DEng), MBSE and SysML

  • Create a Digital Engineering (DEng) Engineering Plan
  • Apply MBSE to DoD5000
  • Working with Models
  • Create SysML Diagrams for a Simple System in the workshop
  • Block Definition Diagrams
  • Internal Block Diagrams
  • Use Case Diagrams
  • Activity Diagrams
  • Sequence Diagrams
  • State Machine Diagrams
  • Constraints and Parametric Diagrams
  • Package Diagrams
  • Requirements Diagrams
  • Allocations




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