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dc.contributor.advisorStephen C. Graves and Randolph E. Kirchain, Jr.en_US
dc.contributor.authorHasik, Matthew Jen_US
dc.contributor.otherLeaders for Manufacturing Program.en_US
dc.date.accessioned2006-11-07T16:54:07Z
dc.date.available2006-11-07T16:54:07Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/34670
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Manufacturing Program at MIT, 2006.en_US
dc.descriptionIncludes bibliographical references (leaves 49-51).en_US
dc.description.abstractAn automotive manufacturer facing decreasing average product volumes as a result of market fragmentation while simultaneously reducing its manufacturing plant footprint must adapt to the difficult challenge of increased product mix within its manufacturing system. The increase in complexity resulting from greater product mix is considered to be a significant driver in increasing plant investment cost and reducing plant operating effectiveness. Thus, the ability to fully understand and more effectively balance the complexity trade-offs associated with different product-to-manufacturing plant allocation scenarios is critically important, as the manufacturer formulates its strategy and analyzes the associated costs and benefits. The ultimate question to be addressed is whether there exists a "complexity threshold" in terms of the maximum number of differentiated body styles (unique vehicle models) to be produced inside a single assembly plant. This thesis analyzes the challenge of manufacturing system and plant complexity by first developing a competitive benchmark study of body-style complexity at the major North American OEMs' plants. Then, manufacturing and operations data is analyzed for evidence of a "complexity threshold" in one manufacturer's operations.en_US
dc.description.abstract(cont.) Finally, a linear-program based optimization model is developed to enable a Manufacturing Planning group to better understand the company's tolerance for plant complexity by quantifying manufacturing costs associated with various product-to-manufacturing plant allocation scenarios. This tool enables the planner to simultaneously consider thousands of different possible combinations of which products to produce in which plants, by analyzing manufacturing investment and per-vehicle operating cost estimates for each combination. The ability to impose constraints on the maximum number of body styles produced at any one plant yields insight on the value of pursuing a higher-mix (in terms of body styles) manufacturing strategy in particular plants, or across the entire plant footprint.en_US
dc.description.statementofresponsibilityby Matthew J. Hasik.en_US
dc.format.extent51 leavesen_US
dc.format.extent3881849 bytes
dc.format.extent3881166 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
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/1721.1/7582
dc.subjectCivil and Environmental Engineering.en_US
dc.subjectSloan School of Management.en_US
dc.subjectLeaders for Manufacturing Program.en_US
dc.titleAn analysis of motor vehicle assembly plant complexity : developing a framework to evaluate the existence of a complexity thresholden_US
dc.title.alternativeDeveloping a framework to evaluate the existence of a complexity thresholden_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentLeaders for Manufacturing Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc71302676en_US


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