2026-09-24T22:26:44Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/91512022-01-13T07:54:52Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Stanley B. Gershwin and Donald Rosenfield.
Wilson, Prentice D. (Prentice Douglas), 1971-
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
Sloan School of Management
2005-08-22T23:07:22Z
2005-08-22T23:07:22Z
2000
2000
http://hdl.handle.net/1721.1/9151
45257911
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.
Includes bibliographical references (leaves 65-66).
Rapidly changing technology and increased competition have made supply chain management and purchasing more and more critical in determining a companies competitiveness. Many industrial firms spend more than one half of every sales dollar on purchased products, and this percentage has been increasing with recent moves towards downsizing and outsourcing. Consequently, more and more pressure is being placed on materials organizations to cut costs and manage supply chains more efficiently. By developing tools that address two of the biggest issues, this project seeks to aid in the cost cutting and supply chain management efforts. The first tool optimizes product demand allocation among suppliers. The second tool controls inventory levels through more accurate inventory targets. Without proper tools to enable optimal demand allocation among suppliers, companies incur excess procurement costs. Most allocation systems do not take supplier capacity and shipping costs into account when allocating demand. Consequently, overall costs are excessive, because individual supplier capacities and demand is not matched to reduce costs for the supply chain as a whole. Many companies set inventory targets that are unattainable without significant risk, because the targets do not accurately represent requirements. Current targets are derived from models that do not include forecasted demand fluctuations, lead-times to individual plants, or variations in lead · times to plants. Therefore, there is an imbalance in true inventory requirements and estimated inventory requirements.
by Prentis D. Wilson, Jr.
S.M.
66 leaves
6881069 bytes
6880830 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Mechanical Engineering.
Managing a global supply chain with durable arm's-length supplier relationships
Thesis
application/pdf
Publication
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unknown
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