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dc.contributor.advisorDaniel Whitney, Scott Keating, and Timothy Gutowski.en_US
dc.contributor.authorBenitez Cardenas, Mauricio Salvador.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.accessioned2019-10-11T22:24:44Z
dc.date.available2019-10-11T22:24:44Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122585
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MITen_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MITen_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 85-86).en_US
dc.description.abstractComposite airplane manufacturing requires the use of autoclaves to cure composite materials in order to create durable, lightweight parts for use in airplanes. The large size, complexity and utility consumption of this equipment makes it an ideal starting place for cost optimization. Cost modeling and the framework created by this research provide input to understand the cost impact of the complex decision between multiple part capacity and single part capacity autoclaves. The results of this research include the identification of cost drivers for the autoclave equipment as focus areas for future cost reduction efforts. Additionally, wait time modeling illustrates how multiple capacity autoclaves increase work in progress and queue lengths and how to assign costs based on the impact of batching to production flow. The framework and analysis also show cost sensitivity to offloading parts and changes in production rates by using linear optimization algorithms to evaluate different scenarios. The framework is extendable to other capital equipment with complex tradeoffs by serving as a starting point for a data driven understanding of costs from recurring, non-recurring and production flow factors.en_US
dc.description.statementofresponsibilityby Mauricio Salvador Benitez Cardenas.en_US
dc.format.extent86 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.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.titleLife-cycle cost modeling and Optimization for capital equipment procurementen_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.oclc1119391607en_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.imported2019-10-11T22:24:43Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentMechEen_US


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