Digital Model-based Engineering: Expectations, Prerequisites, and Challenges of Infusion

August 24, 2018 White Paper

Details

Research Team
Dr. Clifton Baldwin, Mr. Micheal Bisconti, Mr. Jaime Guerrero, Mr. Joe Hale, Dr. Pamela Kobryn, Mr. Geethesh Kukkala, Mr. Midh Mulpuri, Philomena Zimmerman
Universities / Organizations
Stevens Institute of Technology
Department of Homeland Security
Department of Defense
Federal Aviation Administration
National Aeronautics and Space Administration
Department of Veterans Affairs

Abstract

This paper was a collaboration by the Model-Based Systems Engineering (MBSE) Infusion Task Team, formed by the Interagency Working Group on Engineering Complex Systems (IAWG), an informal collaboration of government civilian systems engineering organizations interested in improving systems engineering practice. Inquiries regarding this publication may be directed to the following organization:

Office of the Deputy Assistant Secretary of Defense Systems Engineering

3030 Defense Pentagon 3C167

Washington, DC 20301

Email:  osd.atl.asd-re.se@mail.mil

Description

Executive Summary:

Digital Model-based Engineering (DMbE) is the use of digital artifacts, digital environments, and digital tools in the performance of engineering functions. DMbE is intended to allow an organization to progress from documentation-based engineering methods to digital methods that may provide greater flexibility, agility, and efficiency.

The term “DMbE” was developed as part of an effort by the Model-Based Systems Engineering (MBSE) Infusion Task Team to identify what government organizations might expect in the course of moving to or infusing MBSE into their organizations. The task team was established by the Interagency Working Group on Engineering Complex Systems (IAWG), an informal collaboration among government systems engineering organizations. This paper discusses the work of the MBSE Infusion Task Team to date. The task team identified prerequisites, expectations, initial challenges, and recommendations for areas of study to pursue, as well as examples of efforts already in progress.

The team identified the following five expectations associated with DMbE infusion, discussed further in the body of the paper:

  • Informed decision making through increased transparency, and greater insight
  • Enhanced communication
  • Increased understanding for greater flexibility/adaptability in design
  • Increased confidence that the capability will perform as expected
  • Increased efficiency

The team identified challenges an organization might encounter when looking to infuse DMbE:

  • Assessing value added to the organization. Not all DMbE practices will be applicable to every situation in every organization; and not all implementations will have positive results.
  • Overcoming organizational and cultural hurdles.
  • Adopting contractual practices and technical data management.
  • Redefining configuration management. The DMbE environment changes the range of configuration information to be managed to include performance and design models, database objects, as well as more traditional book-form objects and formats.
  • Developing IT infrastructure. Approaches to implementing critical, enabling IT infrastructure capabilities must be flexible, reconfigurable, and updatable.
  • Ensuring security of the single source of truth.
  • Potential over-reliance on quantitative data over qualitative data. Executable/computational models and simulations generally incorporate and generate quantitative vice qualitative data.

The task team also developed several recommendations for government, academia, and industry, as discussed in the paper. The task team recommends continuing beyond this initial work to further develop the means of implementing DMbE and to look for opportunities to collaborate and share best practices.

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