A4.2 - A Digital Twin Framework for New Generation FTI Management Processes
- Event
- ETTC 2026 - European Test and Telemetry Conference
2026-06-09 - 2026-06-11
Nuremberg - Chapter
- ML & AI I
- Author(s)
- A. T. Kaymak - Turkish Aerospace, Ankara (Turkey), M. Kekec, S. Aydin - Turkish Aerospace, Ankara (Turkey)
- Pages
- 74 - 80
- DOI
- 10.5162/ettc2026/A4.2
- Price
- free
Abstract
In 2024, our study proposed a framework to integrate Flight Test Instrumentation (FTI) Configuration Records -Numbered Parameter Lists (NPL)- with Flight Test Database to establish a ground for an FTI Digital Twin development. This paper aims to present the operational outcomes to date. FTI Configuration Management is evolving into an advanced ecosystem where NPL and flight test big data are merged in one medium, OPTIMUS. Supported with Inventory Management Sub-Module to track assets such as sensor or equipment from warehouse to aircrafts. FTI Digital Twin in its current form features a 3D visualization and within its infrastructure, it communicates with Teamcenter, JIRA and Document Management System to ensure an accessible and traceable configuration management and data integrity. A key point in FTI Digital Twin development is to integrate Artificial Intelligence algorithms and models to support pre-flight operations. System now performs autonomous pre-condition checks for FTI data according to sensor-based rules, such as full-scale or fixed-data validations for sensors. Multiple Deep Learning and ML models are deployed in a selectable model pool to try to identify possible anomalies in real-time sensor data and are re-trained if needed in a feedback loop when necessary. Progressing to the next phase of the project, to analyze similar data characteristics between sensors across flight test campaigns, the software architecture is being established and is progressing through to support predictive maintenance on preparation for flight test campaigns.