An Analysis of Recoverable Item Inventory Systems with Service Facilities Subject to Breakdown,

Abstract

The purpose of this study is to analyze an inventory/maintenance system for recoverable items, that is, items which are subject to repair when they fail. The repair of items is performed by a maintenance facility which has a fixed number of service stations or channels which are also subject to failure. When an item fails, a demand is immediately placed for a like replacement from a spare pool. The failed part is sent to the repair facility to be serviced on a first-come, first-served basis. The spare pool is replenished when repair on the item is completed. When a service station fails, repair is initiated immediately and the failed server is replaced by an operative spare server if one is available. This analysis is limited to a single-echelon system with no outside sources of supply or repair. The objective of this study is to model the system described in order to observe the relationship of system performance to spare stock levels and service facility design. Specifically, the model is used to minimize the total expected unit backorders given an investment constraint on the number of spare items, service channels and spare servers in the system.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA108010

Entities

People

  • Peter L. Knepell

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Differential Equations
  • Equations
  • Kolmogorov Equations
  • Markov Chains
  • Markov Processes
  • Operations Research
  • Partial Differential Equations
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Steady State
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Logistics and Supply Chain Management.
  • Mathematical Modeling and Probability Theory.