Reliability Growth Planning with Reliability Assurance Testing

Abstract

Rapid fielding of new military systems has significantly reduced acquisition program schedules and led to reductions in traditional reliability growth test programs. Bayesian statistical techniques can be helpful in these environments, as they provide a more complete assessment of reliability through the combination of disparate data sources (e.g., different tests or configurations). The model results may also be used to develop assurance test plans, which are the Bayesian analogue to traditional reliability demonstration tests. This report outlines an approach for determining the amount of testing necessary for reliability assurance at the end of a test program, while also aligning these results with a reliability growth test program prior to the assurance test. The approach provides a reasonable path for growing reliability within the constrained environment.

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Document Details

Document Type
Technical Report
Publication Date
Mar 17, 2023
Accession Number
AD1196219

Entities

People

  • Martin Wayne

Tags

Fields of Study

  • Engineering

Readers

  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Life Cycle Cost Analysis
  • Statistical inference.

Technology Areas

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