Basic Research in Reliability for Real Systems.

Abstract

The goal of our research is to develop practical models and efficient algorithms to analyze and evaluate the reliability/availability/maintainability of complex systems in which component failures are statistically dependent and each component is subject to degradations before complete failure. The Event-Based Reliability Model (EBRM) was developed to model and analyze the reliability of a network in which component failures are statistically dependent. In EBRM, the events that could cause component failures were modeled explicitly. This approach required much less parameters than the traditional model employing conditional probabilities. The EBRM was also proved to be a completely general model which could be applied to various types of failure dependencies. For reliability evaluations, many existing algorithms for computing network reliability could be used with minor modifications and no significant increase in computational complexity. An improved algorithm for the approximate evaluation of network performance was also developed. For multi-state systems, ordered enumeration was used to approximate and bound system reliabilities and other performance measures, and an efficient algorithm was developed for this purpose. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 20, 1986
Accession Number
ADA177324

Entities

People

  • Victor O. Li

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Availability
  • Complex Systems
  • Computational Complexity
  • Degradation
  • Maintainability
  • Mathematics
  • Probability
  • Reliability
  • Test And Evaluation

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Statistical inference.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms