Predictive Analytics to Maintain Program Development Speed and Reduce Risk on Test Resources

The Celeris Systems proposal aims to address the Department of the Air Forceĺs (DAF) critical need for enhanced test resource management and predictive maintenance through the integration of advanced analytics. Leveraging its established iRIS platform, Celeris will develop the Holistic Asset Wellness & Knowledge (HAWK) predictive analytics module. This module, powered by commercially-proven AI and machine learning (ML), will enable real-time monitoring and predictive maintenance of test assets, proactively identifying potential issues before they disrupt acquisition schedules. By optimizing resource availability and reducing unplanned downtime, HAWK will enhance mission readiness across key DAF programs, including the F-35, KC-135, and B-21 acquisition offices, as well as the Air Force Test Center (AFTC) and the Air Force Operational Test and Evaluation Center (AFOTEC).áIn Phase I, Celeris will conduct a feasibility study to integrate HAWK with the iRIS Resource Coordination Module (RCM) and evaluate its ability to meet DAFĺs specific operational needs. The study will involve customer and end-user discovery, system-level requirements gathering, and initial technical adaptation for seamless integration into DAFĺs digital engineering ecosystem. The end goal is to establish a proof-of-concept and develop a roadmap for Phase II prototyping and Phase III operational deployment, ultimately driving improvements in test asset utilization and contributing to the DAFĺs strategic goals of improved readiness and cost-effective operations.