Applying ABC analysis to the Navy's inventory management system

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Authors
May, Benjamin
Subjects
Clustering
Random Forest
Bootstrap Forest
Regression Trees
Supply Chain Management
Inventory Control
Spare Parts
Navy Enterprise Resource Planning
ABC Inventory Classification.
Advisors
Atkinson, Michael P.
Ferrer, Geraldo
Date of Issue
2014-09
Date
Sep-14
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
ABC Analysis is an inventory categorization technique used to classify and prioritize inventory items in an effort to better allocate business resources. A items are defined as the inventory items considered extremely important to the business, requiring strict oversight and control. B items are important to the business, but don’t require the tight controls and oversight required of the A items. C items are marginally important to the business. ABC Analysis aims to ensure the business-driving inventory items are effectively and efficiently managed. There are numerous single- and multiple-criteria approaches to implementing ABC Analysis. This thesis presents an analysis and comparison of multiple approaches, as they relate to Navy Weapons Systems Support (WSS) Command’s large National Item Identification Number (NIIN) inventory. Additionally, random forests are grown from the inventory metadata to identify and/or verify the attributes most strongly affecting fleet readiness goals. The model will allow WSS to focus resources not only on the correct NIINs, but in the correct areas of NIIN management. Better WSS resource allocation will result in higher fleet readiness, WSS’s primary goal.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
Sponsors
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.
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