NCMS Project #: 141068
Problem: Having a data platform that not only anticipates when maintenance is actually needed rather than scheduled due to manual input from operator suggestions, but also advises on what parts to have on hand when assets do break, would save U.S. industries substantial time and money, as well as prevent employees from performing redundant maintenance and sustainment tasks. As technology continues to develop and is infused in new and existing platforms there is more vehicle prognostic data becoming available. This enables a new maintenance philosophy of leveraging vehicle data to provide visibility into the asset’s condition while improving availability and decreasing the overall maintenance burden.
Benefit: Many of the processes and technologies are agnostic and applicable to other fleets of vehicles, and lessons learned can be exploited by the commercial industry and other services within the DOD.
Solution/Approach: In Phase I, Abrams condition-based maintenance (CBM) data registration processes were established, and metadata was registered. Hardware to collect Abrams CBM data (the security enhanced MSD) was fielded, and initial data characterization was performed. A disc-based process for delivering data to the Army’s Common CBM Data Warehouse (CCBMDW) was established. For Phase II, a more streamlined network-based approach for delivering data to the CCBMDW will be integrated in preparation for updates to the Army’s logistics network.
Impact on Warfighter:
- Predictive maintenance approach
- Reduce maintenance costs
- Improve asset performance and reliability
- Increase warfighter readiness
- U.S. Army Program Manager, Abrams/Product Directorate Main Battle Tank Systems (PM Abrams/PD MBTS)
- Program Executive Office Ground Combat Systems (PEO GCS)
- Ricardo Defense, Incorporated
- Maintenance avoidance and reliability