Modeling the Contribution of Maintenance Manpower to Readiness and Sustainability.

Abstract

This report describes and simulates a simple queuing model relating the mix of maintenance personnel in a repair station to weapon system availability in dynamic, wartime scenarios. The mixes of manpower considered in the model are described by the number of personnel in each occupation, their skill levels, and their cross-training. It developed to demonstrate the feasibility and importance of modeling a richer mix of manpower while explicitly considering the uncertainties about the true warfare demands for skills. The most important model output is the expected number of weapos systems (aircraft in our applications) non-available (NA) due to missing reparable parts by day of the war. The model provides a framework for illustrating the effects of changes in the types and number so repairmen, spare parts, and job assignment rules on this output. Other outputs include the standard deviation of NA aircraft by day of the war and average time to repair broken parts. Three mixes of manpower are analyzed, each under a base case scenario and two minor variations on that scenario. The first mix contains only one skill level per occupations. The second mix assumes cross-training among personnel; individuals in different occupations are imperfectly substitutable for one another. The third mix introduces an additional skill level per occupation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA164750

Entities

People

  • Glenn A. Gotz
  • Richard E. Stanton

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Attrition
  • Maintenance
  • Maintenance Personnel
  • Manpower
  • Mathematical Models
  • Models
  • Monte Carlo Method
  • Personnel Management
  • Probability
  • Simulations
  • Spare Parts
  • Standards
  • Tactical Aircraft
  • Time Intervals
  • United States
  • Weapon Systems

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Occupational Health and Safety.