Predictive Modeling for Navy Readiness Based on Resource Investment in Supply Support and Maintenance

Abstract

The Navy invests substantial resources to fleet maintenance in terms of part supply, corrective maintenance, maintenance availabilities, and overhauls. In order to measure and prioritize weapon systems investment decisions, an endurance supply metric Es is being developed to ensure these systems are ready for tasking across the full spectrum of operations. This research project will attempt to develop models to determine self-sustaining stock levels of critical parts, for key ship systems, in order to operate for at least T1 days without resupply, with a risk no greater than beta1 that part shortage will cause system failure. These models are developed for both a single deployed ship and multiple deployed ships.

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Document Details

Document Type
Technical Report
Publication Date
Nov 30, 2022
Accession Number
AD1189484

Entities

People

  • Kenneth Doerr
  • Magdi N. Kamel

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Availability
  • Data Mining
  • Data Science
  • Data Sets
  • Deployment
  • Distribution Functions
  • Failure Mode And Effect Analysis
  • Information Science
  • Investments
  • Logistics
  • Maintenance
  • Military Research
  • Monte Carlo Method
  • Order Statistics
  • Predictive Modeling
  • Probability
  • Radar
  • Schools
  • Simulations
  • Spare Parts
  • Standards
  • Statistics
  • Supply Chain
  • Weapon Systems

Readers

  • Life Cycle Cost Analysis
  • Maritime Combat Support and Expeditionary Logistics.