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dc.contributor.advisorStephen C. Graves and Stanley Gershwin.en_US
dc.contributor.authorHolly, Sean Michaelen_US
dc.contributor.otherLeaders for Manufacturing Program.en_US
dc.date.accessioned2007-04-03T17:15:11Z
dc.date.available2007-04-03T17:15:11Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/37132
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M. in Ocean Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2006.en_US
dc.descriptionIncludes bibliographical references (leaf 58).en_US
dc.description.abstractIntel's FAB 17 (F17), in an effort to remain competitive and reduce production cycle time, recently committed to adopt lean manufacturing as their approach to continuous improvement. To aid in this effort, the factory staff has dedicated a group people to develop tools based on lean manufacturing principles. Over the last 18 months, they have created three systematic approaches to address various forms of throughput variation, Autonomous Manufacturing (AM), Planned Maintenance (PM), and Waste Elimination (WE). Autonomous Manufacturing focuses on refurbishing manufacturing tools to new or better condition, up-skilling manufacturing technicians, and differentiating abnormal from normal operating conditions. It is meant to address throughput variation as a direct result of old, poorly maintained tools. Planned Maintenance focuses on keeping refurbished tools in new or better conditions, level loading maintenance activities, and minimizing manufacturing tool downtime due to scheduled maintenance activities. It is meant to address throughput variation as a direct result of tool availability variation. Finally, Waste Elimination focuses on optimizing the flow of information, people, and material.en_US
dc.description.abstract(cont.) It is meant to address throughput variation as a direct result of inefficient flow through the manufacturing process. This thesis provides an overview of F17's lean journey. It shows that F17 has done an excellent job of developing an infrastructure to support their lean transformation. Going forward, their major challenge will be ingraining the new principles into the existing organizational structure. A variation analysis approach uses a simple model of daily production of an operation, several key metrics that relate work in progress (WIP) flow to tool performance, and a graphical display of WIP flow and tool performance. A case study conducted identifies the most probable source of throughput variation as arrivals at one operation, tool performance at another operation, and WIP management at a third operation.en_US
dc.description.statementofresponsibilityby Sean Michael Holly.en_US
dc.format.extent58 leavesen_US
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.titleLean manufacturing in a semiconductor environment : use of variation analysis to focus continuous improvement effortsen_US
dc.typeThesisen_US
dc.description.degreeS.M.in Ocean Engineeringen_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.oclc85777201en_US


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