A METHOD FOR PREDICTING REPAIR-PARTS REPLACEMENT DEVELOPED FROM DATA FOR M60 TANKS AND M113 APCS

Abstract

This technical memorandum describes a method of estimating repair- parts consumption for vehicle fleets during periods of projected future utilization. At the request of the study's Project Advisory Group and interested Army agencies, the methodology developed is capable of using TAERS-type information as input data, and calculating repair-part consumption estimates automatically through the use of a series of computer routines. For any repair parts of interest the first step involves the calculation of replacement rates during individual usage intervals as, for example, each 100 miles of operation. The second step employs standard statistical techniques to provide a means of projecting the usage-dependent replacement rates into the time period under study. In the final step the projected replacement rates are combined with projections of vehicle usage to develop estimates of the number of repair parts that will be replaced during the time period studied. This methodology can be useful in estimating repair-parts consumption throughout the period of utilization of many different end items of equipment for which TAERS data are available. The value of the forecasts obtained, however, depends directly on the accuracy and completeness of the input data utilized.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1966
Accession Number
AD0477428

Entities

People

  • Conway J. Christianson
  • Elizabeth C. Seip
  • Harrison N. Hoppes
  • Howard A. Markham
  • John R. Bossenga

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Armored Personnel Carriers
  • Army Equipment
  • Computer Programs
  • Computers
  • End Items
  • Final Drives
  • Fuel Injection
  • Fuel Injectors
  • Ignition
  • Ignition Systems
  • Inventory
  • Magnetic Tape
  • Plastic Explosives
  • Reliability
  • Shock Absorbers
  • Spark Plugs
  • Statistical Analysis

Readers

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