The Effects of Variability in Demand and Time Parameters for Multi-Item, Multi-Echelon, Multi-Indenture Reparable Inventory Systems

Abstract

This research sought to describe an alternative way for calculating expected back order (EBO) for reparable inventory systems. The high costs associated with reparable items management, together with its importance for system's availability, make the assessment of back orders of great importance in supporting decisions of what-to-buy and where-to-locate those items. Starting at the point that existing models (METRIC, MOD-METRIC, and VARIMETRIC) rely on some assumptions that often cannot be met in real life, the proposed method (called P-METRIC), which is a mix of simulation and mathematical analytical model, relaxes assumptions about Demand, Time to Repair (TTR), and Ordering & Ship Time (OST) distributions looking for potential differences that may cause on the EBO calculation. The study consists of 10 conceptual examples where the parameters of Demand, TTR, and OST vary according to probability distributions recognized by the related literature. It also presents a case study of 20 reparable items of the T-27 Tucano, an advanced-training, light-attack deployed by the Brazilian Air Force. EBO numbers of the existing and proposed models are compared with results gathered from simulation (conceptual examples) and a field research (T-27 Tucano) in order to allow conclusions about the accuracy and suitability of the proposed method.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2002
Accession Number
ADA401517

Entities

People

  • Roberto C. De Abreu

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Business Administration
  • Case Studies
  • Delphi Method
  • Downtime
  • Logistics
  • Maintenance
  • Mathematical Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Simulations
  • Students
  • Systems Engineering
  • Training

Readers

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