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dc.contributor.advisorDaniel Whitney, Arnold Barnett and Kamal Youcef-Toumi.en_US
dc.contributor.authorDiallo, Fatima(Fatima Zahraye)en_US
dc.contributor.otherSloan School of Management.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2020-09-03T15:51:09Z
dc.date.available2020-09-03T15:51:09Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/126897
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 63-64).en_US
dc.description.abstractAs 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.en_US
dc.description.statementofresponsibilityby Fatima Diallo.en_US
dc.format.extent64 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleUsing discrete-event simulation to increase system capacity : a case study of an assembly planten_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentLeaders for Global Operations Programen_US
dc.identifier.oclc1191622832en_US
dc.description.collectionM.B.A. Massachusetts Institute of Technology, Sloan School of Managementen_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Mechanical Engineeringen_US
dspace.imported2020-09-03T15:51:05Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentMechEen_US


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