ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING: APPLICATIONS IN ARMY LOGISTICS

Open Access
Author:
Wonderling, Benjamin Jordan
Area of Honors:
Supply Chain and Information Systems
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Robert Alexander Novack, Thesis Supervisor
  • John Spychalski , Honors Advisor
Keywords:
  • Artificial Intelligence
  • AI
  • Machine Learning
  • Logistics
  • Supply Chain
  • Internet of Things
  • Industry 4.0
  • Army Logistics
  • Military Logistics
  • Change Management
Abstract:
As society and this economy moves into a revolutionary period of technological advancement, commonly referred to as the “Fourth Industrial Revolution” or “Industry 4.0,” organizations will need to adapt accordingly. Industry 4.0 involves critical advancements in artificial intelligence and machine learning that have the ability to change how organizations operate, communicate and strategically execute their inherent goals. Specifically, artificial intelligence and machine learning offer opportunity to improve a supply chain’s efficiency and logistics. While artificial intelligence and machine learning are optimal tools for providing solutions in theory, it is important to understand the feasibility of applications that leverage these tools. One large organization in particular that could benefit from implementing artificial intelligence and machine learning to improve its logistics is the United States Army. This thesis aims to provide an in-depth analysis of artificial intelligence and machine learning, explore application uses in logistics, then determine the feasibility of using artificial intelligence to improve Army logistics. The thesis begins with an overview of artificial intelligence and machine learning, suggests current supply chain applications, and recognizes key players. The thesis will then identify current investments and applications in artificial intelligence and machine learning by the U.S. Department of Defense. Finally, the thesis will provide potential applications in Army logistics as well as present requirements for adoption and recommendations for implementation.