The Allocation of Automated Test Equipment Capacity with Variability in Demand and Processing Rates

Abstract

The purpose of this thesis is to develop a model for allocating the Consolidated Automated Support System (CASS) to the intermediate repair sites. The model uses integer, linear, and nonlinear programming (optimization) to determine the approximate number of CASS stations at a site based on demand, operational availability of the aircraft at the site, budget, and utilization of the CASS stations. The model can be used as a decision tool by NAVAIR PMA 260 to allocate CASS stations to that site. Monte Carlo simulation with Crystal Ball is used to examine the impact of variability on the current and the proposed solution. Determining the number of CASS at a site affects the number of spare parts and the operational availability, and in turn will affect the budget of PMA 260. In this thesis, we develop a decision support tool to assist PMA 260 in making these CASS allocation decisions. Moreover, the most significant contributions are the proof of concept that variable and peak demand can be incorporated into capacity planning (beyond planning for average demand) and linking predicted congestion to operational availability of aircraft (readiness).

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2010
Accession Number
ADA535745

Entities

People

  • Jeremy M. Beckham
  • Mustafa S. Akturk

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Business Administration
  • Computer Programming
  • Computers
  • Linear Programming
  • Load Monitoring
  • Logistics
  • Maintenance
  • Management Personnel
  • Mathematical Models
  • Mathematical Programming
  • Nonlinear Programming
  • Operations Research
  • Optimization
  • Supply Chain
  • Supply Chain Management
  • Test And Evaluation
  • Test Equipment

Readers

  • Logistics and Supply Chain Management.