Wholesale Level Reorder Point and Reorder Quantity Computation During Periods of Declining Demand

Abstract

For several decades the U.S. Navy has used a set of specific mathematical inventory models to help wholesale item managers make management decisions concerning consumable items of material. Implicit in these models is the assumption that the mean of quarterly demand for an item remains constant over time. This assumption is violated often, particularly during periods of force reduction or when equipment is retired. When this declining demand pattern occurs, the inventory models usually keep stock levels too high. This results in excess material known as inapplicable inventory. Recently, inapplicable inventory in the Navy was estimated to be as high as 10.4 billion dollars. Navy logisticians have invested a great deal of effort in solving this problem, mainly by focusing on forecasting. While improved forecasting may reduce inapplicable inventory to some extent, it will not, by itself, solve the problem This research has explored the problem of inapplicable inventory, its model- based causes and alternative solutions. The resulting inventory model, designed to work easily within the existing Navy UICP inventory information system, significantly reduced inapplicable inventory in several simulations which were run in this research.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA260891

Entities

People

  • Charles M. Lilli
  • Claude R. Husson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Calculators
  • Computational Science
  • Computations
  • Computer Programs
  • Computer Simulations
  • Computers
  • Department Of Defense
  • Engineering
  • Information Systems
  • Inventory
  • Inventory Control
  • Lead Time
  • Literature Surveys
  • Operations Research
  • Simulators
  • Test Methods
  • United States

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.