Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2008. / Includes bibliographical references. / In 2006, Pratt and Whitney launched the Global Material Solutions business model aiming to supply spare parts to non-OEM engines with minimum 95% on-time delivery and fill-rate. Lacking essential technical knowledge of the target engines, predictability and associated confidence of the parts demands are very limited. This thesis focuses on exploring alternative and innovative approaches to providing more accurate demand forecasts based on limited information. Approaches including application of fundamental sampling theorems, random walk simulations based on Markov Chain simplification, and sensitivity analysis on incremental scrap rates were introduced. A software tool, based on the sensitivity analysis was introduced for all gas path parts. The methodology could potentially be applicable to industries other than Aerospace. / by Kien K. Ho. / S.M. / M.B.A.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/43833 |
| Date | January 2008 |
| Creators | Ho, Kien K. (Kine Kit) |
| Contributors | David Simchi-Levi and Roy Welsch., Leaders for Manufacturing Program., Leaders for Manufacturing Program at MIT, Massachusetts Institute of Technology. Department of Civil and Environmental Engineering, Sloan School of Management |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 48 leaves, application/pdf |
| 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., http://dspace.mit.edu/handle/1721.1/7582 |
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