MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Using discrete-event simulation to increase system capacity : a case study of an assembly plant

Author(s)
Diallo, Fatima(Fatima Zahraye)
Thumbnail
Download1191622832-MIT.pdf (1.897Mb)
Other Contributors
Sloan School of Management.
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Leaders for Global Operations Program.
Advisor
Daniel Whitney, Arnold Barnett and Kamal Youcef-Toumi.
Terms of use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
As part of its effort to introduce new technology and to improve the manufacturing system for the 777X production line, Boeing has made a significant capital investment in the Composite Wing Center (CWC). The new facility uses highly automated equipment and processes to support the production of components for the 777X. Since many of the automated machines are unique to the Boeing production system, opportunities exist to model and simulate specific machine systems to ensure that work is being performed as efficiently as possible. To date, most of the factory's process equipment has been installed and is operational, providing a production rate of X parts per month. To meet demand, operations will be gradually ramping up to meet the 777X production targets. The ramp-up to the target production rates will be done by a combination of additional equipment installation and process improvement projects. This research study involves the use of Discrete event simulation to provide insight into current cell capability and to identify process bottlenecks. Moreover, the simulation model incorporates process variability, the sequence of process steps within the cell, equipment downtime data, and resource constraints. The resulting simulation model was verified by comparing it to actual system performance. The model analysis and improvement recommendations show significant improvement over the current process in terms of cycle time reduction and production rates increase. In the future, the developed model will be updated regularly and will be used as a tool to monitor system throughput and to evaluate the impact of process changes to the overall system. In addition, the developed framework will be used to help other plants in a similar situation.
Description
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
 
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 63-64).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/126897
Department
Sloan School of Management; Massachusetts Institute of Technology. Department of Mechanical Engineering; Leaders for Global Operations Program
Publisher
Massachusetts Institute of Technology
Keywords
Sloan School of Management., Mechanical Engineering., Leaders for Global Operations Program.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.