A BAYESIAN RELIABILITY GROWTH MODEL

Abstract

A model is presented for the reliability growth of a system during a test program. Parameters of the model are assumed to be random variables with appropriate prior density functions. Expressions are then derived that enable estimates (in the form of expectations) and precision statements (in the form of variances) to be made of (1) projected system reliability at time tau after the start of the test program; (2) system reliability after the observation of failure data. Numerical examples are presented, and extension to multi-mode failures is mentioned.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1967
Accession Number
AD0663279

Entities

People

  • Stephen M. Pollock

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Bayesian Inference
  • Bayesian Networks
  • Data Science
  • Delta Functions
  • Equations
  • Failure Mode And Effect Analysis
  • Information Science
  • Markov Processes
  • Models
  • Notation
  • Observation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Reliability
  • Stochastic Processes
  • United States

Fields of Study

  • Engineering

Readers

  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy