2026-09-18T20:53:32Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1225822021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Steven J. Spear and David Simchi-Levi.
Cryan, Dan David,III.
Sloan School of Management.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.
Leaders for Global Operations Program.
Sloan School of Management
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Leaders for Global Operations Program
2019-10-11T22:24:35Z
2019-10-11T22:24:35Z
2019
2019
2019
https://hdl.handle.net/1721.1/122582
1119391379
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (page 80).
The Boeing Company is the world's largest aerospace company and is constantly evaluating improvement opportunities to the production system. It is of ongoing interest to the company to have to tools to assess new manufacturing sites. Among the required tasks for such an effort, engineers must identify the processes and capabilities that will be needed. A critical element of this study is the system of internal logistics processes that could manage the flow of parts and material throughout a site. Planning the capacity of these processes is difficult when many of the parameters are uncertain and yet to be determined. This thesis proposes a method for estimating capacity requirements of internal logistics processes by employing the concepts of queuing theory and Little's Law. Using this methodology, a process model was developed and validated by discrete event simulation to provide process planners with an understanding of the relationship and importance of numerous parameters. This understanding allows planners and management to assess the capacity requirements of the processes in terms of projected costs and performance. Values of wait times predicted by the proposed model were in strong agreement with values observed from simulation (R-squared of 96.4%; MAPE of 14.9%) suggesting that the proposed methodology represents an easy-to-use and accurate representation of process parameters. In order to improve the applicability of capacity recommendations for Boeing, further refinement is needed of underlying process parameters as well as cost modeling of threshold parameters (k and pn_max).
by Dan David Cryan, III.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
80 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Civil and Environmental Engineering.
Leaders for Global Operations Program.
Designing internal logistics processes for new manufacturing site
Thesis
application/pdf
2019-10-11T22:24:34Z
Publication
Master
Sloan
CivEng
unknown
unknown
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<Abstract>The Boeing Company is the world's largest aerospace company and is constantly evaluating improvement opportunities to the production system. It is of ongoing interest to the company to have to tools to assess new manufacturing sites. Among the required tasks for such an effort, engineers must identify the processes and capabilities that will be needed. A critical element of this study is the system of internal logistics processes that could manage the flow of parts and material throughout a site. Planning the capacity of these processes is difficult when many of the parameters are uncertain and yet to be determined. This thesis proposes a method for estimating capacity requirements of internal logistics processes by employing the concepts of queuing theory and Little's Law. Using this methodology, a process model was developed and validated by discrete event simulation to provide process planners with an understanding of the relationship and importance of numerous parameters. This understanding allows planners and management to assess the capacity requirements of the processes in terms of projected costs and performance. Values of wait times predicted by the proposed model were in strong agreement with values observed from simulation (R-squared of 96.4%; MAPE of 14.9%) suggesting that the proposed methodology represents an easy-to-use and accurate representation of process parameters. In order to improve the applicability of capacity recommendations for Boeing, further refinement is needed of underlying process parameters as well as cost modeling of threshold parameters (k and pn_max).</Abstract>
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