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dc.contributor.advisorSara L. Beckman and David E. Hardt.en_US
dc.contributor.authorAnthony, Richard M. (Richard Morgan), 1971-en_US
dc.contributor.otherLeaders for Manufacturing Program.en_US
dc.date.accessioned2006-11-08T16:31:46Z
dc.date.available2006-11-08T16:31:46Z
dc.date.copyright2004en_US
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/34749
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2004.en_US
dc.descriptionIncludes bibliographical references (p. 81-83).en_US
dc.description.abstractThis thesis describes work completed during an internship assignment at Intel Corporation's process development and wafer fabrication manufacturing facility in Santa Clara, California. At the highest level, this work relates to the importance of adequately creating and maintaining data within IT solutions in order to receive the full business benefit expected through the use of these systems. More specifically, the project uses, as a case example, the sampling methodology used in the fab for metrology data collection to show that significant issues exist relating to the software Various recommendations were undertaken to improve the application's effectiveness. As part of this effort, plans for an online reporting tool were developed allowing much greater visibility into the system's ongoing performance. Initial data updates and other improvements resulted in a reduction in both product cycle times and required labor hours for metrology operations. application database and business processes concerning data accuracy and completeness. The organizational challenges contributing to this problem will also be discussed. Without a rigorous focus on the accuracy and completeness of data within manufacturing execution systems, the results of continuous improvement activities will be less than expected. Furthermore, sharing information relating to these projects across geographical boundaries and business units is vital to the success of manufacturing organizations.en_US
dc.description.statementofresponsibilityby Richard M. Anthony.en_US
dc.format.extent83 p.en_US
dc.format.extent4439649 bytes
dc.format.extent4439455 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Manufacturing Program.en_US
dc.titleAnalyzing sampling methodologies in semiconductor manufacturingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeM.B.A.en_US
dc.contributor.departmentLeaders for Manufacturing Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc56606672en_US


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