| dc.contributor.advisor | David E. Hardt and Stephen C. Graves. | en_US |
| dc.contributor.author | Wang, Yang,M. Eng.Massachusetts Institute of Technology. | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Mechanical Engineering. | en_US |
| dc.date.accessioned | 2021-05-25T18:22:34Z | |
| dc.date.available | 2021-05-25T18:22:34Z | |
| dc.date.copyright | 2021 | en_US |
| dc.date.issued | 2021 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/130840 | |
| dc.description | Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, February, 2021 | en_US |
| dc.description | Cataloged from the official PDF of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 121-122). | en_US |
| dc.description.abstract | To 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.statementofresponsibility | by Yang Wang. | en_US |
| dc.format.extent | 122 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT 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.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Mechanical Engineering. | en_US |
| dc.title | Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. in Advanced Manufacturing and Design | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
| dc.identifier.oclc | 1252628578 | en_US |
| dc.description.collection | M.Eng.inAdvancedManufacturingandDesign Massachusetts Institute of Technology, Department of Mechanical Engineering | en_US |
| dspace.imported | 2021-05-25T18:22:34Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | MechE | en_US |