Dyna-Sim

A Nonstationary Queuing Simulation with Application to the Automated Test Equipment Problem

Louis W. Miller, Richard E. Stanton, Gordon Crawford

Published 1984

This Note describes the Dyna-Sim model, which provides a capability for exploring the implications of maintenance repair queuing for spare parts requirements. Use of the Dyna-Sim model to study the Automated Test Equipment (ATE) problem led to the conclusion that the "ample server assumption" (i.e., that there are more than enough ATE available to serve any repair demands) is misleading for situations where queues become saturated in high sortie rate scenarios. The authors also used Dyna-Sim to show that in a constrained server problem, the choice of the repair time distribution is not important. This permits use of exponential repair distributions in the development of tractable analytical approximations to queuing models.

Document Details

  • Copyright: RAND Corporation
  • Availability: Web Only
  • Year: 1984
  • Pages: 70
  • Document Number: N-2087-AF

Citation

Chicago Manual of Style

Miller, Louis W., Richard E. Stanton, and Gordon Crawford, Dyna-Sim: A Nonstationary Queuing Simulation with Application to the Automated Test Equipment Problem. Santa Monica, CA: RAND Corporation, 1984. https://www.rand.org/pubs/notes/N2087.html.
BibTeX RIS

This publication is part of the RAND note series. The note was a product of RAND from 1979 to 1993 that reported miscellaneous outputs of sponsored research for general distribution.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.