Methodologies for Integration of PHM Systems with Maintenance Data

Abstract

The Automatic logistics program in the Air Force seeks to reduce development, production, and ownership costs for the next generation fighter aircraft by increasing system reliability while reducing maintenance requirements. A large number of technologies are becoming available within the Prognostics and Health Management (PHM) community that will lead to reduced cost and increased availability. The challenge is to develop advanced technology to integrate available PHM information from a variety of different sources into the maintenance and logistics infrastructure. PHM and maintenance/logistics systems must be thoroughly examined and tightly integrated in order to perform maintenance actions in the most efficient way to reduce ownership cost and increase availability. This paper presents multi-agent technology that integrates maintenance and PHM data to provide more effective maintenance identification and scheduling. The proposed methodologies will enable the maintenance and logistics infrastructure to fully benefit from newly developed PHM systems. Additionally, the PHM systems update themselves based on feedback obtained from the maintenance systems. The integration will utilize intelligent software agent technology in order to develop such solutions within open, highly dynamic, uncertain and complex environments with data distributed over a network. This provides benefits such as reusability, scalability, and continuous improvement with dynamically evolving ability.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA498575

Entities

People

  • Fatih Camci
  • G. S. Valentine
  • Kelly Navarra

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Artificial Intelligence
  • Computer Programming
  • Data Analysis
  • Engineering
  • Engineers
  • Failure Mode And Effect Analysis
  • Infrastructure
  • Lead Time
  • Logistics
  • Maintenance
  • Resource Management
  • Scheduling (Production)
  • Software Agents
  • Supervised Machine Learning
  • United States Naval Academy

Fields of Study

  • Computer science
  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Fire Suppression Systems Design.
  • Logistics and Supply Chain Management.