NCMS Project #: 142373
Problem: Global logistics challenges facing the airline, ships and vehicles industries involve a complex operating environment with multiple suppliers and sub-tier suppliers, stove piped Supply Chain Management approaches and varied configurations for their respective fleets. These complexities challenge the effectiveness of supply at the point of need reducing the availability and reliability of the commercial fleets.
Benefit: The project will serve as an example to the commercial industry in providing new ways for commercial aircraft, ship, vehicle industries to improve Supply Chain Management using AI/ML in an integrated data environment.
Solution/Approach: The Phase IV objective is to initially implement and improve an analytical effort to support software for a maintenance organization’s use of Artificial Intelligence/Machine Learning, with advanced mathematical algorithms in Supply Chain Management to demonstrate an increase in parts availability and reduce customer wait time. Phase IV will conduct in-depth analysis of the initial delivery and demonstration at Marine Corps Air Station (MCAS) Yuma and utilize data documentation, data cleaning, and data merging to realize efficiencies of delivered algorithms.
Impact on Warfighter:
- Increase speed of decision making
- Decrease maintenance and sustainment costs
- Enhance mission planning and success rates
DOD Participation:
- U.S. Marine Corps
- Joint Strike Fighter Program Office
- U.S. Air Force (observer)
- U.S. Navy (observer)
Industry Participation:
- SteerBridge Solutions
- NCMS
Benefit Area(s):
- Cost savings
- Repair turnaround time
- Mx avoidance & reliability
- Mx management improvement
- Improved readiness
- Reliability improvement
Mx Focus Area:
- Business IT and Analytics
