Monte Carlo Simulation of Reliability Problems

Abstract

The procedures for analog Monte Carlo simulation of Markov processes are examined. Two variance reduction techniques are then included in a nonanalog formulation to increase the sampling efficiency for highly reliable systems,, and a method for incorporating uncertainty in failure and repair rate data is outlined. Models for three classes of component dependencies appearing in reliability and availability problems are incorporated into the Markov formulation. They are (1) shared repair crews between components, (2) load sharing between components, and (3) standby mode. Results are given for a series of model problems to demonstrate the efficiency of the methods as well as the effects of the dependencies on system unreliability and unavailability.

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Document Details

Document Type
Technical Report
Publication Date
Jun 26, 1985
Accession Number
ADA162811

Entities

People

  • F. M. Skalak
  • H. H. Fong
  • J. Y. Leung
  • K. H. Hsu
  • W. K. Liu

Organizations

  • Northwestern University

Tags

Communities of Interest

  • Air Platforms
  • Cyber
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Differential Equations
  • Engineering
  • Equations
  • Markov Processes
  • Monte Carlo Method
  • New York
  • Nuclear Engineering
  • Pressure Vessels
  • Probability
  • Reliability
  • Risk
  • Risk Analysis
  • Sampling
  • Scientific Research
  • Security
  • Simulations
  • Standards

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Statistical inference.