ESTIMATING THE S-T RELIABILITY FUNCTION USING IMPORTANCE AND STRATIFIED SAMPLING

This paper describes a highly efficient Monte Carlo sampling plan for estimating the sensitivity of the system reliability as the component reliabilities vary over a set of values. Sensitivity analysis becomes an important consideration when contemplating component replacement and alternative system designs, and when accounting for the effect of using sample estimates, based on historical failure data, for the true component reliabilities. The sampling plan is a major advance over most other Monte Carlo proposals which only estimate the system reliability at a single point. The method combines importance and stratified sampling techniques to gain its advantage. In addition to unbiased point estimates, the paper derives individual confidence intervals as well as simultaneous confidence intervals for all the points. It also describes the steps for implementation and illustrates how the plan works in practice.

• Corporate Authors:

  Operations Research Society of America

  Mount Royal and Guilford Avenue
  Baltimore, MD  United States  21202
• Authors:
  • Fishman, G S
• Publication Date: 1989-5

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 462-473
• Serial:
  • OPERATIONS RESEARCH
  • Volume: 37
  • Issue Number: 3
  • Publisher: NEWELL, GORDON F.

Subject/Index Terms

• TRT Terms: Alternatives analysis; Components; Confidence intervals; Estimating; Implementation; Monte Carlo method; Networks; Operations research; Reliability; Sensitivity analysis; Stochastic processes; System design
• Uncontrolled Terms: Replacing
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Research; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 00485677
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 31 1989 12:00AM