Digital Engineering
Digital Engineering in this project refers to the transformation of legacy and new aircraft survivability test data into predictive digital models using advanced AI, vector databases, and data pipelines. It is a data-driven approach to improve design, analysis, and decision-making in aerospace and defense systems. Digital Engineering is a modern approach that uses advanced software, AI models, and data systems to design, analyze, and improve complex systems—without relying solely on physical testing. Instead of just creating hardware prototypes, engineers now work in digital environments that simulate real-world performance using historical and real-time data. In the project presented by Neoskye Inc. for the U.S. Air Force, digital engineering plays a central role in transforming aircraft survivability test data into reusable digital models. These models predict how materials and structures will behave under pressure, impact, temperature, and stress.
→ Reduces redundant testing, improves speed and accuracy of design
→ Links data to CAD tools for early-stage design and optimization
→ Builds material survivability models using historical test data
→ AI adds missing context and insights, ranks results
→ Retrieves best matches using vector similarity
→ Enables natural language queries like “Show stress-strain tables
→ Fine-tuned on Air Force data for accurate prediction
→ Understands context and meaning across data types
→ Processes text, images, and tables together using Vision-Instruct model
→ Enables streaming into AI models and user dashboards