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dc.contributor.advisorCharles L. Cooney and Roy Welsch.en_US
dc.contributor.authorSimpson, Christina M. (Christina Margaret)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2011-09-27T18:36:53Z
dc.date.available2011-09-27T18:36:53Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/66050
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 75-76).en_US
dc.description.abstractThe Novartis BioPharmOps division is responsible for manufacturing large molecule products, including monoclonal antibodies, for late stage clinical trials and commercial sales. The BioPharmOps site in Huningue, France is expanding their product line but is also trying to reduce costs; cost pressures are increasing as biotech products become a larger part of Novartis' pipeline. The site uses a standard cost method to calculate their product costs. However, when using standard costs it can be time-consuming to extrapolate and predict costs when inputs and assumptions (such as product mix or process parameters) are changed. This project describes development of a model that allows the factory to quickly and easily simulate new product mixes and process flows. This model provides the site with a different view of their costs that will help them understand their cost drivers more completely and thereby help enable strategic decision-making at the site. A model of this type can be used to provide unexpected insights but the data in it are not meant to stand alone. By using results from a cost model like this along with operational metrics like throughput time or changeover time, a site should be able to quickly predict the cost impact of process changes or changes in the production plan.en_US
dc.description.statementofresponsibilityby Christina M. Simpson.en_US
dc.format.extent76 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.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleCost modeling for monoclonal antibody 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 Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc752309922en_US


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