Non-Fiction Books:

Simulation of Autonomic Logistics System Sortie Generation

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Paperback / softback
Simulation of Autonomic Logistics System Sortie Generation by Paul D Faas
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Description

The current Air Force logistics operations system is reactive in nature, meaning that after the aircraft detects a part failure, the maintenance person must perform fault isolation procedures and then steps are taken to repair or replace the faulty item. This may or may not include ordering of a replacement item from base supply. The Autonomic Logistics System (ALS) concept changes this reactive process into a proactive one with the employment of technologies such as prognostics and distributed information network. This new approach to the logistics process shows the potential for cost savings, increased aircraft operational availability, and better system performance. The ALS basic function can be compared to the human body's nervous system. The body's nervous system performs activities automatically or without constant thought like respiration and blood circulation. This same concept can be applied to the Air Force logistics system. Certain logistics tasks can be handled automatically or autonomously. Ordering parts for a broken system, calling the right maintenance specialist to the right aircraft reporting a problem, notifying the maintenance control center that a certain aircraft has a malfunctioning system and will not be available for the next sortie, and other possible applications. Since the ALS can handle these routine tasks, the maintenance personnel are free to perform more important tasks such as maintaining and repairing the jets. This thesis explores the impact of this concept on the aircraft sortie generation process by building a discrete event simulation tool to allow the study of the baseline existing system and the ALS.
Release date NZ
November 19th, 2012
Author
Audience
  • General (US: Trade)
Illustrations
Illustrations, black and white
Imprint
Biblioscholar
Pages
108
Dimensions
189x246x6
ISBN-13
9781288314072
Product ID
29997963

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