Vehicle Maintenance and Repair Data Acquisition and Predictive Maintenance (DAPM)

NCMS Project #: 140905

Problem: Currently there is a lot of variation across Army platforms in the ability to collect and transfer this data that creates a significant obstacle to implementing CBM+. GE is proposing to study this problem by incorporating our industrial and software expertise into a test set of Army ground vehicle data to help create a viable solution for the U.S. Army.

Benefit: With access to data that can streamline maintenance and instruct personnel when repairs and updates are actually needed, rather than suggested, reduces asset down time, which translates to less wear and tear on the equipment, lower equipment costs.

Solution/Approach: This specific pilot effort has three primary aims:  demonstrate the ability to collect time-series vehicle data, expand the current sensor footprint to maximize predictive analytics’ capabilities, and to provide visibility into the current condition of vehicles’ and future maintenance requirement.

Impact on Warfighter:

  • Improved readiness
  • Improved maintenance
  • Lower maintenance costs
  • Less emissions
  • Smaller footprint

DOD Participation:

  • U.S. Army TARDEC
  • U.S. Army PMOs, Ground Vehicle Repair & Maintenance

Industry Participation:

  • GE Digital
  • NCMS

Benefit Area(s):

  • Cost savings
  • Repair turn-around time
  • Maintenance avoidance and reliability
  • Maintenance management improvement
  • Improved readiness
  • Reliability improvement

Focus Area:

  • Reliability improvement

Final Report