What is it about?
Novel approach integrating knowledge graphs with artificial intelligence to facilitate value-focused, risk- informed authoritative decision making to enable lifecycle digital materiel management processes to accelerate delivery of materiel capabilities.
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Why is it important?
The fundamental challenges to the digital transformation of materiel systems processes to develop and deliver new capabilities is the need to overcome stovepiped functional knowledge inherent to large organziations as well as the need to accelerate lifecycle processes by transforming from linear document-centric processes to digital, AI- enabled automated process steps to. The integrated knowledge graph / large language model approach presented can overcome both of these challenges to accelerate delivery of new value-focused capabilities.
Perspectives
This paper is a culmination of a personal 12 year journey in developing the concepts of digital engineering. It is also a springboard for introducing AI as the next major advancement in the digital transformation of engineering processes. The explosion of generative AI and Large Language Models when coupled with augmented knowledge management will enable digital engineering practices to achieve the full promise of the ongoing global digital transformation.
Ed Kraft
Edmkraft Inc.
Read the Original
This page is a summary of: A Knowledge-Graph Approach to Digital Materiel Management, January 2025, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/6.2025-1285.
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