System Dynamics Aviation Readiness Modeling Demonstration

Abstract

A proof-of-concept demonstration of System Dynamics modeling was developed to determine the relative merit of the approach and then an experiment compared the results of the System Dynamics model with a traditional linear regression readiness model. This report documents the proof of concept model development and the experiment's results. An aviation readiness production model was formulated using system dynamics. The model was developed over a period of six months with participation from subject matter experts at Commander Naval Air Force and Commander Strike Fighter Wing Pacific. The model incorporates monthly flight hour execution taking into consideration aircraft mission capable rates and the location of a squadron relative to the Fleet Response Plan (FRP) training cycle to generate Primary Mission Area points in strike warfare that are accumulated to generate an Attack Index. Concurrently, a renewed Strike Warfare Proficiency (Strike PRO) analysis was conducted for comparison. Twenty-four Carrier Air Wing (CVW) events at NSAWC Fallon, NV were used to benchmark performance. The results of the Strike PRO algorithm and the results of the System Dynamics Model were each compared against the performance metric. Source code for the System Dynamics Model is included as an appendix to the report.

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Document Details

Document Type
Technical Report
Publication Date
Aug 31, 2005
Accession Number
ADA436605

Entities

People

  • Michael E. Mcdevitt

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aerial Warfare
  • Air Force
  • Aircrafts
  • Computer Programs
  • Databases
  • Deployment
  • Fighter Aircraft
  • Information Science
  • Information Systems
  • Lessons Learned
  • Logistics
  • Maintenance
  • Reliability
  • Spreadsheet Software
  • Statistical Tests
  • Supply Chain
  • Warfare

Readers

  • Aerospace Engineering
  • Aerospace logistics and air mobility.
  • Computational Modeling and Simulation