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dc.contributor.advisorCharles Cooney and Steven Spear.en_US
dc.contributor.authorDonohue, Michael (Michael Tiahrt)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2011-09-27T18:38:53Z
dc.date.available2011-09-27T18:38:53Z
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/66066
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, June 2011.en_US
dc.description"June 2011." Page 42 blank. Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 41).en_US
dc.description.abstractOne of the most challenging problems in Amgen's biological manufacturing facility is adhering to the daily schedule of production tasks. Delays in non-time critical tasks have been traced to temporary workload surges that exceed the production staff's capability to handle them. To quantify this effect, a method for creating an M/M/c queueing model that is specific for bulk biologic manufacturing processes was developed. The model was successfully validated by comparing the predicted results to the historical data for each of the five production shifts. A discussion of how to model different improvement programs is presented, and Amgen-specific data are presented. It was found that across-the-board task duration reductions will reduce the schedule deviation rate by up to 50%. Additionally, it is shown that implementing staff-cross training with other production areas will reduce the schedule deviation rate between 14% and 75%. Implementation aspects of these improvement initiatives in a regulated production environment are discussed.en_US
dc.description.statementofresponsibilityby Michael Donohue.en_US
dc.format.extent42 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.titleApplication of queueing theory in bulk biotech 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. Engineering Systems Division
dc.contributor.departmentSloan School of Management
dc.identifier.oclc753704812en_US


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