Hybrid Stochastic Models for Remaining Lifetime Prognosis

Abstract

The United States Air Force is developing its next generation aircraft and is seeking to reduce the risk of catastrophic failures, maintenance activities, and the logistics footprint while improving its sortie generation rate through a process called autonomic logistics. Vital to the successful implementation of this process is remaining lifetime prognosis of critical aircraft components. Complicating this problem is the absence of failure time information; however, sensors located on the aircraft are providing degradation measures. This research has provided a method to address at least a portion of this problem by uniting analytical lifetime distribution models with environment and/or degradation measures to obtain the remaining lifetime distribution.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA426813

Entities

People

  • Steven M. Cox

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Aircrafts
  • Computational Science
  • Data Science
  • Differential Equations
  • Failure Mode And Effect Analysis
  • Fighter Aircraft
  • Information Science
  • Kalman Filters
  • Knowledge Management
  • Mathematical Filters
  • Random Variables
  • Regression Analysis
  • Statistical Algorithms
  • Two Dimensional
  • United States

Readers

  • Aerospace logistics and air mobility.
  • Life Cycle Cost Analysis
  • Theoretical Analysis.