Fiscal Year	2023
Division	Research & Sponsored Programs
Department	Naval Research Program
Investigator(s)	Chen, Hway-Jen Koyak, Robert A.
Sponsor	NPS Naval Research Program (Navy)
Summary	In recent years submarines undergoing maintenance at U.S. shipyards have experienced increases in maintenance delays, idle time, and unplanned work for maintainers. This trend has resulted in increasing maintenance costs and reduced availability (Ao). Factors driving this trend cited by GAO (2020) include IT infrastructure, including software without predictive capabilities. Our effort will examine the extent to which this shortfall can be addressed by employing AI and ML techniques to data collections held at NAVSEA that bear on the usage and condition of systems on selected vessels of the Navy¿s submarine fleet. Taken in conjunction with information from the Material Readiness Database (MRDB), we will derive prognostic metrics such as the predicted time to failure that can be used to better manage maintenance availability periods. In particular, the use of optimization techniques for managing maintenance with the metrics will be examined.
Keywords	Data analysis, submarine availabilities, machine learning, artificial intelligence, operational availability (Ao)
Publications	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal