Equipment and Supply Readiness
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Authors
O'Halloran, Bryan
Subjects
readiness
maintenance modeling
maintenance analysis
data analysis
cost analysis
ground vehicles
data modeling
data visualization
maintenance predictions
program planning
resource planning
resource allocation
maintenance modeling
maintenance analysis
data analysis
cost analysis
ground vehicles
data modeling
data visualization
maintenance predictions
program planning
resource planning
resource allocation
Advisors
Date of Issue
2022-10-22
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Headquarters Marine Corps, Programs and Resources, Marine Corps Systems Command, and Fleet Marine Forces desire a model that will enhance the understanding of the equipment readiness issues and needs experienced with the Secure, Mobile, Anti-Jam, Reliable, Tactical Terminal (SMART-T) and Joint Light Tactical Vehicle (JLTV) programs. Equipment maintenance information coupled with the model will provide insight into different resource allocation options available to improve the readiness of these systems. This knowledge will aid in decisions for which resources are applied to improve equipment readiness. The systems engineering capstone team developed a step-wise model to input equipment maintenance data, transform the data to a useable state, perform categorical analysis, and conduct equipment cost analysis. To foster the data-driven model, equipment maintenance data was provided to the systems engineering capstone team for both the SMART-T and JLTV systems. The maintenance data spanned multiple years for each system and included 42 unique fields associated with each maintenance record. This data-driven approach to develop the model allowed for several types of analysis to be performed on the data sets. Overall, the model developed provides the ability to visualize maintenance rates based on primary defect codes which can alert analysts to changes in expected or historical maintenance rates. These changes could be a sign of future problems and enable the Marine Corps to act prior to these potential issues develop into a problem with a significant impact. The model can also predict future maintenance needs which can be used to allocate resources appropriately to handle the expected maintenance load.
Type
Poster
Description
NPS NRP Project Poster
Series/Report No
Department
Systems Engineering (SE)
Organization
Naval Research Program (NRP)
Identifiers
NPS Report Number
Sponsors
Funding
This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE0605853N/2098). https://nps.edu/nrp
Chief of Naval Operations (CNO)
Chief of Naval Operations (CNO)
Format
1 p.
Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.