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dc.contributor.advisorStanley Gershwin.en_US
dc.contributor.authorDaigle, Sean (Sean Michael)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.date.accessioned2017-05-11T19:58:32Z
dc.date.available2017-05-11T19:58:32Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/108972
dc.descriptionThesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 97).en_US
dc.description.abstractThis thesis is a compilation of the analysis and recommendations gathered from two industry projects conducted at Applied Materials Varian Division in Gloucester, MA and at the MIT Lincoln Laboratory in Lexington, MA. This thesis addresses the improvement of a quality metric used at Applied Materials through the means of material shortage reduction and lead time reduction of system sub-assemblies. Manufacturing quality was found to be impacted by material shortages across the facility and capacity constraints in an area of the facility that manufactures equipment subassemblies. Implementing a new inventory policy would result in an expected 74% to 80% reduction in material shortage occurrences. The capacity increase recommended in this thesis would reduce average lead time for sub-assemblies from about 5-6 days to under 2 days. At the MIT Lincoln Lab, this thesis addresses a possible approach to improving the accuracy of production scheduling and delivery date quotes through the use of job shop scheduling software and historical data analysis. The recommended fabrication request delivery date prediction process involves using a scheduling software to find the optimal delivery date for a job, and then adding a Shop Capacity Buffer time that is calculated using historical data on schedule delays. Schedule delays can be caused by a variety of random events that occur in machine shops, such as machine failures or operators falling ill. By selecting a Shop Capacity Buffer of 90%, a 90% on-time completion rate should be observed. This new method would achieve improved results from the 75% on-time completion rate at present. The final recommendation is a policy change that aims to characterize sources of delay and accurately compensate for the delay using the Shop Capacity Buffer in the delivery date quote process..en_US
dc.description.statementofresponsibilityby Sean Daigleen_US
dc.format.extent97 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleQuality improvement, inventory management, lead time reduction and production scheduling in high-mix manufacturing environmentsen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Advanced Manufacturing and Designen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc986497121en_US


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