CBM+ Data Characterization for AI-Based Predictive Maintenance Analysis
NCMS Project #: 141012
Problem: A condition where an industry is plagued with excessive down time due to low equipment reliability and sub-optimized maintenance creates a substantial negative impact on our country’s aviation operations as well as the cost and quality of air transportation services sold to the general public. There is a critical need to benchmark current and emerging industry standards initiatives which could be utilized by the Services to support the assessment, characterization, collection and transformation of condition-based maintenance plus (CBM+) data and information, to enable enterprise-wide predictive maintenance applications using artificial intelligence (AI).
Benefit: While data generation, collection, storage and retrieval capabilities have kept pace via technology developments, the capability to develop and apply appropriate AI-based analytical methods and tools to analyze and make use of the sensor data at a commensurate rate has been severely lagging. By focusing on developing a solution that provides a replicable, standard process that supports the assessment and characterization of sensor and maintenance event data for AI-based analysis, this project directly targets the issues that industry is facing today.
Solution/Approach: Predictive maintenance applications are essential in order to deliver optimum levels of aircraft availability and sustainment operations efficiencies. The initial phase will provide a clear insight to assess and establish a foundation that demonstrates the value of using a standardized process specification to support the assessment and characterization of sensor and maintenance event data for a given aircraft (health-ready) component or subsystem to determine if the data is sufficient to support AI-driven analysis. Efforts will focus on issues specific to the H-60 platform.
Impact on Warfighter:
- Reduce forward deployed asset footprint
- Re-prioritize maintenance activities
- Lower costs
- Improve warfighter readiness
DOD Participation:
- Joint Artificial Intelligence Center (JAIC)
- Army, Air Force, Navy, Marines and Special Operations Command (SOCOM)
- H-60 Program Offices
Industry Participation:
- Global Strategic Solutions LLC
- GE Aviation
- Carnegie Mellon University, Auton Lab
- University of Tennessee, The Bredesen Center
- NCMS
Benefit Area(s):
- Cost savings
- Repair turn-around time
- Positive environmental impact
- Safety
- Maintenance management improvement
Focus Area:
- CBM+