2026-09-19T19:44:54Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1044032022-01-28T17:56:44Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Daniel Whitney and Karen Zheng.
Belkina, Tamara
Leaders for Global Operations Program.
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Sloan School of Management
2016-09-27T15:15:25Z
2016-09-27T15:15:25Z
2016
2016
http://hdl.handle.net/1721.1/104403
958277860
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 59).
This dissertation presents the results of developing optimization algorithms for use in operational scheduling of airplane stalls and paint hangars at the Boeing Company's Everett Delivery Center. With the increasing number of orders, more airplanes are coming out of the Everett Factory and into the flightline for painting, fueling, and other pre-delivery testing activities. While Boeing's existing infrastructure is still well able to support this increasing scale of operations, some of the existing manual scheduling processes become more time consuming and sprout inefficiencies. This existing scheduling process was mapped and analyzed, and an Excel VBA tool was developed in collaboration with Boeing's Applied Math group to provide visibility into cost avoidance opportunities for the Everett Delivery Center. As a result of this work, up to 35% of paint hangar costs have been identified as potentially avoidable.
by Tamara Belkina.
M.B.A.
S.M. in Engineering Systems
59 pages
eng
Massachusetts Institute of Technology
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
Sloan School of Management.
Institute for Data, Systems, and Society.
Engineering Systems Division.
Leaders for Global Operations Program.
Optimizing large-volume scheduling for cost avoidance
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>This dissertation presents the results of developing optimization algorithms for use in operational scheduling of airplane stalls and paint hangars at the Boeing Company's Everett Delivery Center. With the increasing number of orders, more airplanes are coming out of the Everett Factory and into the flightline for painting, fueling, and other pre-delivery testing activities. While Boeing's existing infrastructure is still well able to support this increasing scale of operations, some of the existing manual scheduling processes become more time consuming and sprout inefficiencies. This existing scheduling process was mapped and analyzed, and an Excel VBA tool was developed in collaboration with Boeing's Applied Math group to provide visibility into cost avoidance opportunities for the Everett Delivery Center. As a result of this work, up to 35% of paint hangar costs have been identified as potentially avoidable.</Abstract>
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