Using simulation, data mining, and knowledge discovery techniques for optimized aircraft engine fleet management Conference Paper

abstract

• This paper presents an innovative methodology that combines simulation, data mining, and knowledge-based techniques to determine the near- and long-term impacts of candidate aircraft engine maintenance decisions, particularly in terms of life-cycle cost (LCC) and operational availability. Simulation output is subjected to data mining analysis to understand system behavior in terms of subsystem interactions and the factors influencing life-cycle metrics. The insights obtained through this exercise are then encapsulated as policies and guidelines supporting better life-cycle asset ownership decision-making. 2006 IEEE.

name of conference

• Proceedings of the 2006 Winter Simulation Conference

authors

• Erraguntla, Madhav

published proceedings

• PROCEEDINGS OF THE 2006 WINTER SIMULATION CONFERENCE, VOLS 1-5

author list (cited authors)

• Painter, M. K., Erraguntla, M., Hogg, G., & Beachkofski, B.

citation count

• 26

complete list of authors

• Painter, Michael K||Erraguntla, Madhav||Hogg, Gary L Jr||Beachkofski, Brian

publication date

• December 2006

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n0891-7736ISSN  Journal

keywords

• 33 Built Environment And Design
• 3302 Building
• 40 Engineering
• 46 Information And Computing Sciences
• 4605 Data Management And Data Science

Digital Object Identifier (DOI)

• 10.1109/WSC.2006.323221

International Standard Book Number (ISBN) 10

• 1424405017

International Standard Book Number (ISBN) 13

• 978-1-4244-0500-8

start page

• 1253

end page

• +

URL

• http://dx.doi.org/10.1109/wsc.2006.323221