Summaries - Office of Research & Innovation
Back Improving Marine Corps Logistics with Model-driven Big Data
|Division||Research & Sponsored Programs|
|Department||Naval Research Program|
Sanchez, Susan M.
McDonald, Mary L.
Upton, Stephen C.
Kelton, William D.
Lucas, Thomas W.
|Sponsor||NPS Naval Research Program (Navy)|
|Summary||The Marine Corps Logistics Command uses complex models to help manage the Corps’ materiel. These models help LOGCOM better understand the potential impacts and risks that operations and changes in policy may have on various units’ sustainability and readiness. Some of these models contain a large number of input variables, many of which are uncertain. They also generate an enormous amount of output data. This project will identify and enhance the analytic utility of the selected Marine Corps logistics model by embedding it in a data farming environment. A data farming environment: (1) allows analysts to run more experiments by means of a computing cluster, (2) runs the experiments efficiently by using state-of-the-art design of experiments, and (3) gleans insights through the use of data mining and advanced statistical techniques. The end capability will enable Marine Corps analysts to quickly run more experiments over a broader set of factors—thus ensuring that the results are robust. Another benefit is that the new methods will help us identify gaps in our data and how best to mitigate uncertainties. The carefully chosen experiments will provide better big data—by design. Marine Corps officer-students will apply and assess the new capabilities in a LOGCOM directed study.|
|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|