IMPROVING MARINE FORCES STORAGE CENTER EFFICIENCY USING WORKFLOW MODELING AND DISCRETE EVENT SIMULATION
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Authors
Ayres, Kevin J.
Subjects
warehousing
work flow
storage
modeling
discrete event simulation
optimization
logistics
supply chain
material handling
Marine Corps Logistics Command
Marine Force Storage Center
work flow
storage
modeling
discrete event simulation
optimization
logistics
supply chain
material handling
Marine Corps Logistics Command
Marine Force Storage Center
Advisors
Buss, Arnold H.
Ferrer, Geraldo
Date of Issue
2019-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
This thesis uses conceptual modeling and discrete event simulation (DES) to assess warehousing efficiency for Marine Forces Storage Center (MFSC), Marine Corps Logistics Command. In April 2018, MFSC took possession of a new warehouse aboard Marine Corps Logistics Base-Albany to consolidate multiple warehousing operations into one warehouse facility to store, issue, receive, and account for military equipment. In August 2018, MFSC began the consolidation process and started moving all military equipment into one single facility. Today, MFSC conducts warehousing in a 57,000-square-foot storage facility, significantly smaller than the 120,000-square-foot facility it operated in previously. First, simulation event graphs illustrate the specific warehouse workflow behaviors and procedures. Simkit, a Java-based simulation package, is used to build a DES to represent the warehouse workflow processes, compute statistical outputs, and assess the warehousing performances based on different input values. This study analyzes the warehouse throughput using different statistical analysis methods, such as simulation experiments and predictive modeling, to reveal the input-output relationships that promote optimal warehouse performance. The warehouse workflow simulation model serves as a proof of concept and verification tool to promote workflow optimization, identify and mitigate bottlenecks in the workflow processes, and assist data driven decision-making to improve operating procedures.
Type
Thesis
Description
Series/Report No
Department
Computer Science (CS)
Organization
Identifiers
NPS Report Number
Sponsors
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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.