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dc.contributor.advisorDavid E. Hardt and Stephen C. Graves.en_US
dc.contributor.authorWang, Yang,M. Eng.Massachusetts Institute of Technology.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.date.accessioned2021-05-25T18:22:34Z
dc.date.available2021-05-25T18:22:34Z
dc.date.copyright2021en_US
dc.date.issued2021en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/130840
dc.descriptionThesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, February, 2021en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 121-122).en_US
dc.description.abstractTo survive in the global marketplace today that is more dynamic and complex than ever, companies must have a proper and up-to-date material flow design to ensure agile and resilient operations. The importance of monitoring and controlling flow has been made even more apparent with the recent COVID-19 pandemic. Therefore, this work aims to study the material flow system at a leading global manufacturing company, identify problems and gaps in its process, and leverage lean manufacturing methodologies and RFID technology to optimize the material flow of an electronic Kanban (eKanban) system that involves third-party vendors. This thesis outlines a systematic problem-solving approach, starting with process visualization through Value Stream Mapping (VSM), problem identification by issue tree, and benefit analysis via simulation modeling. System design of a Radio-Frequency Identification (RFID) network is performed at both rack-level and item-level by testing RFID hardware, tags, and various system setups. A web interface is developed for data integration and visualization. The successful pilot run demonstrates the effectiveness of the optimized system in eliminating waste and increasing operational efficiency and provides a guide for a full-scale implementation.en_US
dc.description.statementofresponsibilityby Yang Wang.en_US
dc.format.extent122 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleOptimization of material flow by lean tools and RFID integration into a vendor-involved eKanban systemen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Advanced Manufacturing and Designen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.identifier.oclc1252628578en_US
dc.description.collectionM.Eng.inAdvancedManufacturingandDesign Massachusetts Institute of Technology, Department of Mechanical Engineeringen_US
dspace.imported2021-05-25T18:22:34Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentMechEen_US


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