Advancing Cost-Effective Readiness by Improving the Supply Chain Management of Sparse, Intermittently-Demanded Parts

Abstract

Many firms generate revenue by successfully operating machines such as welding robots, rental cars, aircraft, hotel rooms, amusement park attractions, etc. It is critical that these revenue-generating machines be operational according to the firm s target or requirement; thus, assuring sustained revenue generation for the firm. Machines can and do fail, and in many cases, restoring the downed machine requires spare part(s), which are typically managed by the supply chain. The scope of this research is on the supply chain management of the very sparse, intermittently-demanded spare parts. These parts are especially difficult to manage because they have little to no lead time demand; thus, modeling via a Poisson process is not viable. The first area of our research develops two new frameworks to improve the supply chain manager s stock policy on these parts. The stock polices are tested via case studies on the A-10C attack aircraft and B1 bomber fleets. Results show the AF could save $10M/year on the A10 and improve support to the B1 without increasing inventory. The second area of our research develops a framework to integrate the supply chain processes that generate these service parts. With the integrated framework, we establish two new forward-looking metrics. We show examples how these forward-looking metrics can advance the supply chain manager s desire to know what proactive decisions to make to improve his/her supply chain for the good of the firm.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2015
Accession Number
ADA616877

Entities

People

  • Gregory H. Gehret

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Case Studies
  • Commerce
  • Engineering
  • Experimental Design
  • Inventory
  • Knowledge Management
  • Lead Time
  • Literature Surveys
  • Load Monitoring
  • Logistics
  • Operations Research
  • Spare Parts
  • Supply Chain
  • Supply Chain Management
  • Time Intervals

Fields of Study

  • Business
  • Computer science

Readers

  • Defense Acquisition Program Management
  • Economics
  • Educational Psychology

Technology Areas

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