Understanding the Limits of Artificial Intelligence for Warfighters: Volume 3, Predictive Maintenance

Abstract

ISSUE: The U.S. Air Force (USAF) deploys flying units with readiness spares packages (RSPs) to try to ensure that the units are stocked with enough parts to be self-sufficient for 30 days. Predicting which parts are likely to fail-- and, therefore, which parts should be included in the RSPs --is important because overstocking can be expensive and understocking can threaten mission readiness. In this report, we consider whether and when artificial intelligence (AI) methods could be used to improve RSP failure analysis, which currently assumes a probability distribution.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2024
Accession Number
AD1218294

Entities

People

  • Anthony Jacques
  • Li A. Zhang
  • Yusuf Ashpari

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Aircrafts
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Information Systems
  • Logistics
  • Logistics Management
  • Machine Learning
  • Maintenance
  • Neural Networks
  • Operations Research
  • Space Force
  • Supply Chain
  • Supply Chain Management
  • United States
  • Warfare

Readers

  • Artificial Intelligence
  • Logistics and Supply Chain Management.
  • Maritime Combat Support and Expeditionary Logistics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy