Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2006. / Includes bibliographical references (p. 83-84). / Advances in medicine rely on accurate data that is rapidly provided. It is therefore critical for the Genome Sequencing platform of the Broad Institute of MIT and Harvard to continually strive to reduce cost, improve throughput, and increase the quality of its data output. In the past, new technology in the form of both chemistry improvements and robotics has allowed the Institute to achieve these goals in a step-wise manner. However, as the rate of technology progression in sequencing has slowed, the Institute has been forced to look to continuous, incremental improvement in order to achieve its goals. The Core Sequencing/Detection group handles the high-throughput sequencing duties at the Broad Institute. Through the use of robotics and cutting edge biology, they are able to process and sequence upwards of 50 billion bases of DNA per year. The work that this thesis was based on took place primarily in this automated production area. This thesis utilizes a number of lean concepts, including the 7 Wastes and pull production control. / (cont.) Kanban systems, workflow changes, and a 5S implementation were used to bring these concepts to life at the Broad Institute. In order to correctly size the kanban system, process buildup diagrams and discrete event simulation were used. Each of these tools helped to drive the process towards the Institute's goals of reducing cost and improving quality and throughput. / by Kerry P. Person. / S.M. / M.B.A.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/37248 |
| Date | January 2006 |
| Creators | Person, Kerry P. (Kerry Patrick) |
| Contributors | Jeremie Gallien and Charles L. Cooney., Leaders for Manufacturing Program., Leaders for Manufacturing Program at MIT, Massachusetts Institute of Technology. Department of Chemical 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 | 104 p., 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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