LEVERAGING PREDICTIVE ANALYTICS TO ASSESS 7TH FLEET SUSTAINMENT
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Authors
Stevens, Edwin J.
Subjects
global distribution chain
supply
logistics
data sciences
pull and push logistics
sustainment
demand prediction
route optimization
supply
logistics
data sciences
pull and push logistics
sustainment
demand prediction
route optimization
Advisors
Appleget, Jeffrey A.
Zhao, Ying
Date of Issue
2020-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Increasing operational availability through logistics readiness is critical to ensure maximum safety and capability of forward deployed ships. The increased operational tempo that forward deployed ships encounter causes high impact failures that affect operational availability and the commander’s decision-making process. As forward deployed 7th fleet ships encounter casualties, unacceptable operational impacts such as out-of-stock or “redlines” occur. Repair rates may be improved by leveraging predictive analytics to understand failure data. Critical systems such as propulsion, communications, or radar are our primary focus. Areas for optimization are identified through statistical analysis of data that we have collected from 7th Fleet organizations such as NAVSUP, NAVSUP WSS, NAVSEA, CTF-73, and SURFGRUWESTPAC. We analyzed and sorted the data to identify any trends and risks that may not currently be tracked. We assessed distributions of potential failure rates, and a peacetime model was developed using Lexical Link Analysis, and then analyzed used JMP. Using our model, potential situations are built to analyze the output and optimize wait times within the constraints of manpower, funding, and availability. Future work using this model may include efforts to evolve to Phase II operations, with increased naval presence resulting in increased sustainability needs, simulated in SIMIO to test casualty and repair rates, as is shown in sample models in this thesis.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
N4
Funder
Format
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.