Reducing Maintenance Costs Through Predictive Analysis
NCMS Project #: 140813
Problem: Controlling maintenance costs is a critical to commercial industry in order to secure and retain market share/competitive advantage. Reducing maintenance cost is also a critical mission for the Defense Department in today’s budget-constrained environment. The challenge, however, is finding ways to make maintenance more efficient and more effective simultaneously; controlling costs while increasing the readiness of fielded platforms. One of the most promising avenues for delivering enhanced maintenance performance is in the area of data analytics, specifically in using data collected by sensors on military assets to predict, and hence avoid, costly failures. The Defense Department could benefit significantly from leveraging OEM-agnostic predictive analytics solutions developed by and for commercial industry to transform from planned to proactive maintenance strategies for its critical equipment.
The Navy surface fleet provides a unique opportunity for a test bed in this regard. The fleet has the advantages of: 1) operating its assets on a more continuous basis and for longer stretches than most aircraft or ground vehicles are run; 2) utilizing propulsion and power technologies that are often identical to those used in industrial and commercial marine applications; and 3) having already invested in the instrumentation and connectivity to collect data on ships and then aggregate and analyze it on shore. The Navy has utilized this data in a variety of ways but has focused largely on parts replacement; it has thus lagged behind leading commercial companies in extracting value from the data it collects.
Benefit: By focusing on the required analytic solutions to tap into the potential value of this CBM data in a timely manner, and enabling proactive CBM actions to be taken prior to failure, this initiative directly targets the issues that industry and the military is facing in keeping pace with the mountain of collected data, and serves as a template process for addressing the challenges associated with supporting fielded assets.
Solution/Approach: Using the Navy fleet as a pilot test bed for proving the utility of these analytics in a military use case could give the broader military community confidence in the approach. After considerable research and interaction with industry, the Navy has decided to pilot GE’s SmartSignal technology, which has been used for over 15 years to monitor a wide variety of equipment for asset-intensive industries such as oil and gas production, power generation, civil aviation, mining, and others.
In this initiative, the Navy and GE will partner to: develop a concrete estimate of SmartSignal’s return on investment, demonstrate the value of SmartSignal’s predictive analytics and diagnostics, and identify and document features and functionality to achieve CBM+ objectives.
Impact on Warfighter:
- Understand of best practices and new modeling techniques
- Advanced warning of major failures
- Reduced maintenance
- Better fuel efficiencies for mechanized assets
- Reduced costs
- Improved readiness
DoD Participation:
- U.S. Navy (NAVSEA)
- OSD-Led Joint Service CBM+ Action Group
Industry Participation:
- GE
- NCMS
Technology Focus Area(s):
- Cost savings
- Repair turnaround time
- Maintenance avoidance & reliability
- Maintenance management improvement
- Improved readiness