A METHODOLOGY FOR ESTIMATING EXPECTED USAGE OF REPAIR PARTS, WITH NO USAGE HISTORY,

Abstract

In the paper a model is presented which focuses on the problem of predicting demands for items with extremely low usage rates. These form the bulk of repair parts in military systems. The basic notion underlying the model is the pooling of usage data for common design items with movement for the purpose of estimating usage rates for similar items which have shown no movement. A unique feature of the model is that it also makes possible the estimation of usage rates for items newly introduced into a system for which no previous usage history is available. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 28, 1970
Accession Number
AD0705511

Entities

People

  • Rosedith Sitgreaves
  • Sheldon E. Haber

Organizations

  • George Washington University

Tags

Fields of Study

  • Computer science

Readers

  • Logistics and Supply Chain Management.
  • Neural Network Machine Learning.
  • Statistical inference.