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Advanced aerospace procurement models with sensitivity analysis and optimized demand allocation

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dc.contributor.advisor Donald B. Rosenfield and David Simchi-Levi. en_US
dc.contributor.author Kary, Jason R en_US
dc.contributor.other Leaders for Manufacturing Program. en_US
dc.date.accessioned 2007-04-03T17:14:33Z
dc.date.available 2007-04-03T17:14:33Z
dc.date.copyright 2006 en_US
dc.date.issued 2006 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/37126
dc.description Thesis (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 Manufacturing Program at MIT, 2006. en_US
dc.description Includes bibliographical references (leaves 69-71). en_US
dc.description.abstract The impact of the sourcing function on the profitability of U.S.-based manufacturing firms is more significant than ever. Today, the purchased component of the cost of goods sold for many firms is more than fifty-percent of sales.' As the volume of purchased material grows every year, and the sourcing function impacts corporate profitability more and more, it has become critical that effective analysis techniques and cost models are used in the development and execution of sourcing strategies. Perhaps the most critical element of the sourcing process is the determination of the optimal supplier or portfolio of suppliers who will be responsible for providing purchased materials. This thesis explores the allocation of outsourced material demand to the supply base in the aerospace industry. A significant portion of this research involves the development of a framework to support a strategic sourcing organization in the determination of the most appropriate portfolio of suppliers for a group of similarly manufactured parts. This framework combines total cost sensitivity analysis and demand allocation programming. en_US
dc.description.abstract (cont.) The results of this thesis are intended to present sourcing managers with a framework that can be applied when comparing U.S.-based manufacturers to low-cost international suppliers. The total cost sensitivity analysis enables the sourcing manager to evaluate the impact of supply chain dynamics including tax rates and currency fluctuation, as well as variations in supplier performance on procurement decisions. Using the total cost model output, a sourcing manager is then able to apply the demand allocation programming model to determine the optimal supplier portfolio given aerospace industry constraints and the operational requirements of the organization studied. The demand allocation programming model is developed as a mixed integer linear program (MILP). The basis for the thesis analysis was a six month internship with a major U.S. aerospace OEM. The research was based on hands-on commodity management experience, literature review, and work with sourcing, finance, and operations professionals. en_US
dc.description.statementofresponsibility by Jason R. Kary. en_US
dc.format.extent 80 leaves en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.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.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Sloan School of Management. en_US
dc.subject Engineering Systems Division. en_US
dc.subject Leaders for Manufacturing Program. en_US
dc.title Advanced aerospace procurement models with sensitivity analysis and optimized demand allocation en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.description.degree M.B.A. en_US
dc.contributor.department Sloan School of Management. en_US
dc.contributor.department Massachusetts Institute of Technology. Engineering Systems Division. en_US
dc.contributor.department Leaders for Manufacturing Program. en_US
dc.identifier.oclc 85775078 en_US


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