autonomous systems, critical machinery, data analytics, data infusion, physicsbased methods, preventive maintenance, sensor systems, structural health management
Autonomous systems have become an integral part of our military operations. Availability and reliability of autonomous systems are critical to mission success. Proactive maintenance is the key enabler for system availability and reliability. Technology advancements including advanced sensor systems, high-performance computing, physics-based prediction methods, advanced data analytics, and machine learning have opened the door for enhanced situation awareness and proactive, condition-based maintenance. The proposed activity will leverage the results of AVT-305 (Research Specialists’ Meeting on “Sensing Systems for Integrated Vehicle Health Management for Military Vehicles” to be held in Athens, Greece, 12-14 December 2018), and the on-going effort of AVT-ET-184 (“Physics of Failure for Military Platforms”) and AVT-ET-185 (“Goal-driven, Multi-Fidelity Approaches for Military Vehicle System-Level Design”) to examine the challenges, special requirements, and enabling technologies associate with proactive maintenance technologies for autonomous military systems. In addition, the team will leverage the on-going efforts as part of the Technical Cooperation Program’s (TTCP) “Naval Exploitation of Energy Data Sets (NEEDS) Collaborative Project” and the naval platform “Structural Health Monitoring Collaborative Project”. The proposed activity will cover air, sea, and ground military autonomous systems to the extent possible. The primary areas to be examined initially will be critical machinery systems and structural health management. During the ET working period (1 Jan 2019 – 31 Dec 2019), the exploratory team will examine the interest level of including the study of other related technology areas.
The proposed exploratory team will attempt to cover the following scientific topics:
(1) Challenges and special requirements for maintenance of autonomous military systems
(2) Maintenance related sensing systems for autonomous military systems
(3) Data driven techniques for system state diagnosis, prognosis, and reasoning
(4) Data infused physics-based methods for prediction of maintenance needs
(5) Other related technology areas of interest to the panel members