Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013. / Cataloged from PDF version of thesis. "June 2013." / Includes bibliographical references (pages 107-109). / As some of the most technically complex systems in the world, United States fighter aircraft require a complex logistics system to sustain their reliable operation and ensure that the day-to-day Air Force missions can be satisfied. While there has been a lot of attention among academics and practitioners regarding the study of this complex logistics system, most of the focus has been on availability of spare parts that are indeed essential for the smooth operations of the fighter aircraft. However, in recent years there has been an increasing awareness that maintenance resources are an equally important enabler and should be considered together with inventory issues. The maintenance resources required to repair the fighter aircraft are expensive and therefore limited. Moreover, there are various types of maintenance that compete for the same resources. It .is therefore imperative that the allocation of maintenance resources is done as efficiently as possible. In this thesis, we study two areas of fighter aircraft maintenance that could significantly benefit from improved resource allocation and scheduling strategies. We use quantitative and qualitative data from Air Force data-bases and logistics personnel to develop an innovative modeling framework to capture these challenging maintenance problems. This modeling framework is based on a generalization of the of the well-known multi-armed bandit superprocess problem. Using these models, we develop index policies which provide intuitive, easily implemented, and effective rules for scheduling maintenance activities and allocating maintenance resources. These policies seem to improve on existing best practices within the Air Force, and perform well in extensive data-driven simulated computational experiments. The first area is focused on the challenges of scheduling maintenance for the low observable (stealth) capabilities of the F-22 Raptor, specifically, maintenance of the outer coating of the aircraft that is essential to maintain its radar invisibility. In particular, we generate index policies that efficiently schedule which aircraft should enter low observable maintenance, how long they should be worked on, and which aircraft should fly in order to maximize the stealth capability of the fleet. Secondly, we model the maintenance process of the F100-229 engine, which is the primary propulsion method used in the F-16C/D and F-15E aircraft. In particular, we generate index policies to decide which engines should take priority over others, and whether or not certain components of the engines should be repaired or replaced. The policies address both elective (planned) and unplanned maintenance tasks. / by John M. Kessler. / S.M.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/82873 |
| Date | January 2013 |
| Creators | Kessler, John M. (John Michael) |
| Contributors | Retsef Levi and Thomas Magnanti., Massachusetts Institute of Technology. Operations Research Center., Massachusetts Institute of Technology. Operations Research Center. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 109 pages, application/pdf |
| Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/7582 |
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