Intelligent Collaborative Aging Aircraft Parts Support

Abstract

Department of Defense (DoD) depot-level maintenance activities often experience delays in obtaining consumable repair and replacement parts for aging aircraft systems and components. As part of a concerted effort to reduce these delays, the Defense Logistics Agency (DLA) sought design, development, and prototyping of Intelligent Collaborative Aging Aircraft Parts Support (ICAAPS) . LMI, in partnership with JWK International, explored the use of data mining and analysis techniques to improve long-range projections of depot-level maintenance requirements for the DLA-managed consumable parts. During a prototype demonstration involving standard depot-level maintenance for C-2 aircraft at the Naval Air Depot in North Island, CA, use of ICAAPS analytical tools improved the forecast accuracy for each consumable part included in the initial test sample. Consequently, continued use of ICAAPS should facilitate more timely consumable parts support and enable reductions in the number and duration of DoD depot-level maintenance delays caused by consumable parts shortages.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2002
Accession Number
ADA408775

Entities

People

  • David A Calderwood
  • Galbraith D. Williams
  • Lawrence P. Forsley
  • Robert L. Jordan

Organizations

  • LMI

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Aircrafts
  • Data Analysis
  • Data Integration
  • Data Mining
  • Department Of Defense
  • Failure Mode And Effect Analysis
  • Landing Gear
  • Logistics
  • Logistics Management
  • Maintenance
  • Maintenance Personnel
  • Maintenance Requirements
  • Models
  • Procurement
  • Prototypes
  • Standards

Readers

  • Aerospace Engineering
  • Logistics and Supply Chain Management.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy