dc.contributor.advisor | Donald B. Rosenfield and Duane Boning. | en_US |
dc.contributor.author | Hwang, Irene S | en_US |
dc.contributor.other | Leaders for Manufacturing Program. | en_US |
dc.date.accessioned | 2007-11-16T14:30:13Z | |
dc.date.available | 2007-11-16T14:30:13Z | |
dc.date.copyright | 2007 | en_US |
dc.date.issued | 2007 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/39593 | |
dc.description | Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2007. | en_US |
dc.description | Includes bibliographical references (leaves 47-48). | en_US |
dc.description.abstract | Significant inventory write-offs have recently plagued ATI Technologies, a world leader in graphics and media processors. ATI's product-centric culture has long deterred attention from supply chain efficiency. Given that manufacturing lead time exceeds customer order lead time for its semiconductors, ATI relies heavily on their demand forecasting team to instigate supply chain activities. The PC business unit forecasting team translates market information into product-line forecast and also sets finished goods inventory levels intended to offset demand uncertainty. Today's inventory decisions are made in response to customer escalations, often ignoring financial implications. To add necessary rigor when setting these inventory levels, this thesis presents a model using wafer and unit cost, profit margin, product lifecycle stage and historical forecast error to categorize products into inventory risk levels. The resultant risk levels become a critical input to monthly demand-supply meetings with marketing, operations and senior executives - the outcome of which are wafer orders and assembly and test plans at the world's largest contract foundries and subcontractors. Finally, the 2006 acquisition of ATI by Advanced Micro Devices (AMD) offers unforeseen flexibility, scale and challenges to the outsourced semiconductor supply chain. | en_US |
dc.description.statementofresponsibility | by Irene S. Hwang. | en_US |
dc.format.extent | 48 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 | Electrical Engineering and Computer Science. | en_US |
dc.subject | Leaders for Manufacturing Program. | en_US |
dc.title | Optimizing inventory levels using financial, lifecycle and forecast variance data | 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 | Leaders for Manufacturing Program at MIT | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
dc.contributor.department | Sloan School of Management | |
dc.identifier.oclc | 175977693 | en_US |