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dc.contributor.advisorJulie A. Shah and Roy E. Welsch.en_US
dc.contributor.authorHerrera, Jason (Jason Richard)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2013-11-18T20:41:06Z
dc.date.available2013-11-18T20:41:06Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/82484
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics; in conjunction with the Leaders for Global Operations Program at MIT, 2013.en_US
dc.descriptionThis electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from department-submitted PDF version of thesisen_US
dc.descriptionIncludes bibliographical references (p. 62-64).en_US
dc.description.abstractThe Boeing Company is looking to bring aircraft manufacturing technology into the 21st century. As part of this process, several projects have been started to develop the technologies required to achieve Boeing's vision for the future of aircraft manufacturing. To date, much of this work has focused on hardware, including robotic and other automation technologies. However, in order to use this hardware, a significant effort must also be made in the area of factory control and coordination. This thesis advances knowledge in this area by evaluating the suitability of different control system approaches for aircraft wing box assembly. First, general classes of control systems are discussed and several criteria are proposed for evaluating their performance in an aircraft manufacturing environment. The current wing box assembly process is then examined in order to develop simplified but representative task networks to which various algorithms can be applied. The Tercio algorithm, developed at MIT, is used to generate schedules for several problem structures of interest in order to characterize the algorithm's performance in this context. The Tercio algorithm is then benchmarked against the Aurora scheduling tool, showing that Tercio can generate more efficient schedules than Aurora, but at the cost of increased computation time. Next, management considerations with respect to product design, manufacturing technology development, and implementation associated with advanced manufacturing technologies are discussed. Finally, recommendations are provided for how Boeing can accelerate the development of useful and practical advanced, automated manufacturing systems.en_US
dc.description.statementofresponsibilityby Jason Herrera.en_US
dc.format.extent64 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectAeronautics and Astronautics.en_US
dc.subjectSloan School of Management.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleEvaluation of control systems for automated aircraft wing manufacturingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeM.B.A.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.contributor.departmentSloan School of Management
dc.identifier.oclc862232623en_US


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