Digital Twin of Defense Industrial Base Workforce

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Authors: Kevin Hasse
Cited by: 0

Abstract

A Digital Twin has been developed to model the Defense Industrial Base (DIB) and aerospace workforce, with a focus on emerging technologies related to Digital Engineering and Advanced Manufacturing. The Digital Twin includes elements that model conceptual jobs, defined by Subject Mater Expert (SME) interviews, to develop and integrate these new technologies into system lifecycles. The job definitions are based on specific areas of needed skills in the workforce, and redefine the job with a goal of setting aside legacy constraints in order to complete the organization’s objectives. The job definitions include data for ongoing duties of the role, tasks that accomplish meaningful units of work supporting the duty, and the knowledge, skills, tools, and behaviors that enable employees to complete the tasks. The model provides a view of supply and demand parameters for the job and workforce skills availability and training capacity. Real time data gathering and analysis on job openings and workforce capacity and competency is integrated with the modeled job characteristics. The job market data is linked to the conceptual job analysis to understand trends in demand for the newly defined jobs, shifting abilities needed, how well qualified potential candidates are prepared for the needed abilities, and how fit for purpose the available training programs are to prepare individuals for the jobs. The Digital Twin helps fill the need of planning for needs to effectively integrate new technology into the DIB, how to train a capable workforce, and how to handle changes affecting the DIB, such as technology migration, aging workforce, surge production, and supply chain disruption. The model may be applied to help identify and optimize training and curriculum development opportunities. Analysis can include regional workforce availability, tiered supply chain readiness, and identification of transferable skills from alternate system design, manufacturing and sustainment industries.

Fields of Study & Subjects

Digital Transformation in Industry Competency Development and Evaluation AI and HR Technologies

Publication details

Journal / source
AIAA SciTech Forum
Publication date
8 January 2026