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dc.contributor.advisorCharles Cooney and Steven Spear.en_US
dc.contributor.authorSmith, Stephen Een_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2011-09-27T18:36:40Z
dc.date.available2011-09-27T18:36:40Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/66048
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; 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. 71-73).en_US
dc.description.abstractGenzyme's manufacturing and supply chain organization is responsible for the production and delivery of medically necessary medicines for patients with rare diseases around the world. Because of the nature of the products produced at Genzyme, a lapse in operational performance has societal as well as economic impacts. Therefore increased understanding of the complex production systems at Genzyme is helpful to reduce risk and improve performance. This thesis is an analysis of a system of two critical production processes at Genzyme. These processes are studied collectively because shared resources make them a tightly coupled system. The research is presented in three sections. The first section explores the current state of the system and explains general performance trends. The second section examines the impact of scheduling complexity arising from shared resources. The third section discusses how process improvement methodologies could be applied at Genzyme. The following conclusions arise from the work conducted for this thesis. First, the performance of the system has declined due to an increase in utilization and an already high level of variability. Second, variability caused by shared resource conflicts can be minimized using new scheduling techniques. And finally, continuous improvement methods are recommended to further reduce variability and increase overall process performance.en_US
dc.description.statementofresponsibilityby Stephen Smith.en_US
dc.format.extent73 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.subjectEngineering Systems Division.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleProcess management applications in biopharmaceutical drug productionen_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. Engineering Systems Division
dc.contributor.departmentSloan School of Management
dc.identifier.oclc752305381en_US


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