Predictive Maintenance Applied Research
Abstract
This effort develops and characterizes artificial intelligence (AI) and machine learning (ML) tools and capabilities to intelligently predict and analyze maintenance status for emerging and legacy aviation and ground platforms; extracts maintenance data from databases, sensor data and inference of missing data via virtual simulations investigating maintenance concepts that employ AI data capture and integrate AI tools into enterprise resource planning for military aviation and ground vehicles. Platforms of focus are prioritized by cost and value to Army missions and potentially include the UH60, AH64, CH47, Stryker, and Abrams. Each platform will be sequentially evaluated both at the appropriate component (i.e. engine health) and fleet level. This research enables use of predictive maintenance to increase fleet operational readiness through reduced downtime by preventing critical failure during missions, maximizing availability to combatant commands. Findings will be used to construct a robust Army wide predicative maintenance platform that will accelerate the pace of innovation for this problem set. This platform includes data engineering, pipelines, AI development eco-system, and application delivery. All outcomes will be used to inform requirements and technical architectures for modernization efforts of next generation aviation and ground systems both manned and unmanned. The cited work is consistent with Under Secretary of Defense for Research and Engineering priority focus areas and the Army Modernization Strategy. Work in this Project supports the Army Science and Technology Ground Portfolio and the Joint Artificial Intelligence Center (JAIC) Work in this Project is performed by the United States (US) Army Futures Command.
Document Details
- Document Type
- Project
- Publication Date
- Oct 01, 2022
- Source ID
- CN7_0602180A_2_2040_PB_2022
Related Documents
- Root: Artificial Intelligence and Machine Learning Technologies
- Child Accomplishment: Predictive Maintenance