Military Personnel Flight Customer Wait Time Reduction Model Using Simulation

Abstract

Customers at Military Personnel Flights (MPFs) have been experiencing long wait times. These customers are typically employees of the United States Air Force and every moment spent waiting for service is a moment they are away from their actual jobs. By reducing the mean wait time of MPF customers, manhours can be saved and customer complaints may be alleviated. This research uses data collected from an MPF to build a discrete-event simulation model of an MPF. A full factorial experimental design was conducted in the model using xC;five factors. The factors included the total number of employees, the total number of terminals designated for walk-in customers, the total number of terminals designated for appointment customers, the minimum number of employees working during lunch, and different appointment policies. The outputs of the experiment were used to generate regression models that estimate the mean wait time for walk-in and appointment customers. The analysis showed that the number of employees working has the largest impact on mean wait times when compared against other factors.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2022
Accession Number
AD1170674

Entities

People

  • Nicholas C. Anderson

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Data Science
  • Department Of Defense
  • Employment
  • Engineering
  • Engineers
  • Experimental Design
  • Governments
  • Health Services
  • Information Science
  • Knowledge Management
  • Literature Surveys
  • Military Personnel
  • Operations Research
  • Personnel Management
  • Simulations
  • Standards
  • Statistical Analysis
  • Terminals
  • United States
  • United States Government

Readers

  • Logistics and Supply Chain Management.
  • Mathematical Modeling and Probability Theory.
  • Military Logistics and Supply Chain Management