Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system

Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, February, 2021 === Cataloged from the official PDF of thesis. === Includes bibliographical references (pages 121-122). === To survive in the global marketplace today tha...

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Main Author: Wang, Yang,M. Eng.Massachusetts Institute of Technology.
Other Authors: David E. Hardt and Stephen C. Graves.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2021
Subjects:
Online Access:https://hdl.handle.net/1721.1/130840
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-1308402021-05-28T05:20:00Z Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system Wang, Yang,M. Eng.Massachusetts Institute of Technology. David E. Hardt and Stephen C. Graves. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, February, 2021 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 121-122). 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. by Yang Wang. M. Eng. in Advanced Manufacturing and Design M.Eng.inAdvancedManufacturingandDesign Massachusetts Institute of Technology, Department of Mechanical Engineering 2021-05-25T18:22:34Z 2021-05-25T18:22:34Z 2021 2021 Thesis https://hdl.handle.net/1721.1/130840 1252628578 eng 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. http://dspace.mit.edu/handle/1721.1/7582 122 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Mechanical Engineering.
spellingShingle Mechanical Engineering.
Wang, Yang,M. Eng.Massachusetts Institute of Technology.
Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
description Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, February, 2021 === Cataloged from the official PDF of thesis. === Includes bibliographical references (pages 121-122). === 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. === by Yang Wang. === M. Eng. in Advanced Manufacturing and Design === M.Eng.inAdvancedManufacturingandDesign Massachusetts Institute of Technology, Department of Mechanical Engineering
author2 David E. Hardt and Stephen C. Graves.
author_facet David E. Hardt and Stephen C. Graves.
Wang, Yang,M. Eng.Massachusetts Institute of Technology.
author Wang, Yang,M. Eng.Massachusetts Institute of Technology.
author_sort Wang, Yang,M. Eng.Massachusetts Institute of Technology.
title Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
title_short Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
title_full Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
title_fullStr Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
title_full_unstemmed Optimization of material flow by lean tools and RFID integration into a vendor-involved eKanban system
title_sort optimization of material flow by lean tools and rfid integration into a vendor-involved ekanban system
publisher Massachusetts Institute of Technology
publishDate 2021
url https://hdl.handle.net/1721.1/130840
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