Russell Peak

Digital engineering (DE) is “an integrated digital approach that uses authoritative sources of systems’ data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. A DE ecosystem is an interconnected infrastructure, environment, and methodology that enables the exchange of digital artifacts from an authoritative source of truth.” (DAU, 2017) Digital transformation is fundamentally changing the way acquisition and engineering are performed across a wide range of government agencies, industries, and academia and is characterized by the integration of digital technology into all areas of a business, changing fundamental operations and how results are delivered in terms of new value to customers. It includes cultural change centered on alignment across leadership, strategy, customers, operations, and workforce evolution. In 2020, the Systems Engineering Research Center (SERC) developed a Digital Engineering Competency Framework (DECF) to support the US Department of Defense (DoD). This paper provides an update to the DECF (version. 1.1) and a mapping of some existing DoD training resources against the DECF. It discusses gaps and provides a few high‐level recommendations on how to build DE competency in the DoD acquisition workforce. Though the DECF and the training included here are specific to the DoD, the competency framework is intended to be relevant to anyone working in the DE space.

As systems become more software intensive and complex, managing their development and implementation also becomes more complex. Models in development today are isolated, domain-specific artifacts that are created throughout the design lifecycle. A mechanism is needed to integrate the design models with simulation environments as the models are being developed and refined in order to rapidly see the impacts as the design matures. The ability to perform verification, validation, and accreditation (VV&A) early in the modeling process and throughout the lifecycle could greatly improve the model and its contribution. But in order to perform VV&A on complex systems, a precise language would be required to model these systems in an integrated fashion to remove ambiguity and the segmented developmental lifecycle. Objectives of this research included exploring the unique capabilities of Architectural Analysis and Design Language (AADL) for developing high confidence (verified and validated) models as part of a system development lifecycle and to determine the maturity of the AADL tools for VV&A model refinement. This report has two parallel components where the first component is focused on an AADL approach and exploits synergies and the other component is focused on a SYSML based approach.

To evaluate the opportunities and extent to which open standards can be used in or enhanced for product lifecycle management frameworks, we have developed three metrics, namely, compatibility, completeness, and coverage, for assessing the degree-of-openness of engineering information. A simple test case shows that each of the three metrics provides a certain type of assessment of the degree-of-openness.