NCMS Project #: 142018
Problem: Most private and government ship owners/operators have urgent needs to improve their operations, especially in the area of condition-based asset management, by using new digital technology. They face serious challenges in data collection and data quality management as well as in the development of digital twin and decision support tools. The Naval Surface Warfare Center, Philadelphia (NSWC-PD) is working to address these issues for the Navy. NSWC-PD is particularly interested in demonstrating how current best practice digital analytics could be applied to a class of ship for which little analysis has been undertaken to date.
Benefit: The intent of this initiative is to use the Navy’s LSD 49 as a surrogate for any ship with underutilized data that could be leveraged to generate significant improvements in reliability, availability, maintainability, and overall asset management strategy. Bringing these advances to the commercial marine industry supports the U.S. economy and will bring many benefits to the general public.
Solution/Approach: The project will focus on the use of digital technology (including machine learning and predictive analytics) to extract value from data to support effective decision-making regarding in-service maintenance and sustainment through a ship’s lifecycle. The goal is to take existing data for selected critical systems that are common across both government/military and commercial ships and demonstrate the value that best industry practice digital analytics can provide for ship operations, maintenance, and sustainment/life extension.
Impact on Warfighter:
- Reduce risks
- Predictive insights for decision-makers
- Increase efficiencies and productivity
- Decrease maintenance and sustainment costs
- Extend lifecycle of fleets of assets
- Improve warfighter readiness and lethality
- U.S. Navy Naval Surface Warfare Center-Philadelphia Division (NSWC-PD)
- American Bureau of Shipping (ABS)
- Cost savings
- Repair turn-around time
- Maintenance management improvement
- Improved readiness
- Reliability improvement