Early Life-Cycle Prediction of Reliability

Abstract

The intent of this project is to investigate a variety of approaches for the development of a basic model for the early life-cycle prediction of reliability (pre-Milestone A). The United States Department of Defense (DoD) currently utilizes an acquisition framework in which system development advances through a series of checkpoints known as milestones. Each milestone represents a decision point, with Milestone A being the earliest in the life cycle. At Milestone A, also known as the risk-reduction decision, the DoD evaluates design concepts while also committing funds to the maturation of technologies in an effort to mitigate future risks. Typically, little is known about the particular system to be developed at this point in the acquisition life cycle, but DoD regulations require program man-agers to submit system reliability information (OUSD[A and S] 2015). Traditional reliability predictions, however, require extensive knowledge of the system of interest to produce accurate results. This level of knowledge is unavailable at or before Milestone A, there-fore, there is a need to create models and methodologies for the prediction of system reliability. This report provides an overview of a variety of methods investigated to improve the prediction of early life cycle reliability.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2022
Accession Number
AD1199584

Entities

People

  • Christina H. Rinaudo
  • George E. Gallarno
  • Matieu L. Lagarde
  • Randy K. Buchanan

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Aircrafts
  • Bayesian Networks
  • Business Administration
  • Computational Science
  • Data Analysis
  • Data Mining
  • Department Of Defense
  • Engineering
  • Engineers
  • Failure Mode And Effect Analysis
  • Ground Vehicles
  • Information Science
  • Logistics
  • Regression Analysis
  • Reliability
  • Supply Chain Management
  • Systems Engineering
  • Test And Evaluation
  • United States

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Defense Acquisition Program Management