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dc.contributor.advisorDave Hardt and John Carrier.en_US
dc.contributor.authorRoss, Michael C.M.B.A.Sloan School of Management.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.accessioned2020-09-03T16:47:57Z
dc.date.available2020-09-03T16:47:57Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/126988
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 PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 89-90).en_US
dc.description.abstractVariations and the negatives effects it causes on production capacity and planning are topics of significant interest in the manufacturing communities. This research investigates the hypothesis that, when operating in a highly constrained environment, capacity can be gained by reducing the variations within the system. This study tests this hypothesis through simulation, data analysis, and controlled testing on the variations responsible for limiting capacity at Vektek LLC. The variability in lead times, quality, batch ordering, and demand forecasting contributes to the Bullwhip Effect. This increase in variability will cause excessive inventory, overtime costs, unacceptable service levels, high production costs, and large lead times. This research reduces these variabilities by isolating each cause of variability and placing standard work around it, such as SOPs. Once isolated and controlled, variations were methodically reduced, and significant capacity was gained. The research results show us that the overall variations were reduced by 26.5%. Due to this: overtime costs were reduced, late shipments were reduced by 40.0%, WIP inventories were reduced by 38.0%, and lead times were reduced roughly 22%. The total monetary value saved is estimated to be $988k and the total capacity gained was 30.8%. These results provide an initial validation that reducing the variations will increase the capacity.en_US
dc.description.statementofresponsibilityby Michael C. Ross.en_US
dc.format.extent92 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.titleReducing variations in a highly constrained environment in order to increase production capacityen_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.oclc1191226286en_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.imported2020-09-03T16:47:53Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentMechEen_US


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