<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T06:32:37Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/120244" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/120244</identifier><datestamp>2026-06-06T00:56:30Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">David E. Hardt.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Batra, Rushil</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Mechanical Engineering</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2019-02-05T16:00:40Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2019-02-05T16:00:40Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/120244</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1083130354</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 103-105).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This thesis presents a strategic roadmap laid out for Waters Corporation, an analytical laboratory instrument company, and explores various avenues for digitalization, automation, optimization and standardization throughout its value chain. It then focuses on operational analysis of two pilot process improvement projects at their Global Distribution Center (GDC). Sub-optimal inventory placement caused by randomized assignment of primary storage locations is one of the key challenges faced by GDC. This often leads to inefficiencies in the form of unfulfilled orders as well as additional time and effort expended by material handlers. To cater to this problem, the first project revolves around the development of an inventory location optimization algorithm by taking into consideration the order frequency for a particular product and its distance from the shipping area. This work develops a mathematical formulation for assigning discrete storage location costs as an input for the algorithm by incorporating the nuances of current operating procedures. Preliminary estimates point toward savings of around 5% in walking time. While the aforementioned algorithm improves efficiency for put-away and retrieval of products, GDC requires better technology to track inventory and tackle the challenge effectively. Radio Frequency Identification (RFID) is an Automatic Identification (Auto-ID) technology popular for reading multiple tags at once and not requiring line of sight and. Its implementation was selected as the second pilot project for its ability to better manage inventory, reduce dock-to-stock time, improve put-away and shipping accuracy thereby directly impacting rate and quality of order fulfillment. The estimates suggest a reduction of over 20% in receiving time and 80% in time taken for inventory cycle counts besides drastic improvement in process accuracy. This work analyses the impact of both projects on the existing business processes by assessing the as-is state and proposing a future state after full-scale implementation. RFID has seen limited implementation in the industry owing to complexity in estimating the added value. The suitability of RFID application for inventory management in GDC is demonstrated through a cost-benefit analysis and Net Present Value (NPV). While there are significant costs associated with the technology, the range of applications and benefits derived strengthen the case for its implementation.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Rushil Batra.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng. in Advanced Manufacturing and Design</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">105 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT 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.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Operational analysis of an inventory location optimization algorithm and RFID implementation in a distribution center</dim:field>
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   	&lt;Title>Operational analysis of an inventory location optimization algorithm and RFID implementation in a distribution center&lt;/Title>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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        	&lt;DisplayName>Batra, Rushil&lt;/DisplayName>
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    &lt;Keyword>Mechanical Engineering.&lt;/Keyword>
   	&lt;Abstract>This thesis presents a strategic roadmap laid out for Waters Corporation, an analytical laboratory instrument company, and explores various avenues for digitalization, automation, optimization and standardization throughout its value chain. It then focuses on operational analysis of two pilot process improvement projects at their Global Distribution Center (GDC). Sub-optimal inventory placement caused by randomized assignment of primary storage locations is one of the key challenges faced by GDC. This often leads to inefficiencies in the form of unfulfilled orders as well as additional time and effort expended by material handlers. To cater to this problem, the first project revolves around the development of an inventory location optimization algorithm by taking into consideration the order frequency for a particular product and its distance from the shipping area. This work develops a mathematical formulation for assigning discrete storage location costs as an input for the algorithm by incorporating the nuances of current operating procedures. Preliminary estimates point toward savings of around 5% in walking time. While the aforementioned algorithm improves efficiency for put-away and retrieval of products, GDC requires better technology to track inventory and tackle the challenge effectively. Radio Frequency Identification (RFID) is an Automatic Identification (Auto-ID) technology popular for reading multiple tags at once and not requiring line of sight and. Its implementation was selected as the second pilot project for its ability to better manage inventory, reduce dock-to-stock time, improve put-away and shipping accuracy thereby directly impacting rate and quality of order fulfillment. The estimates suggest a reduction of over 20% in receiving time and 80% in time taken for inventory cycle counts besides drastic improvement in process accuracy. This work analyses the impact of both projects on the existing business processes by assessing the as-is state and proposing a future state after full-scale implementation. RFID has seen limited implementation in the industry owing to complexity in estimating the added value. The suitability of RFID application for inventory management in GDC is demonstrated through a cost-benefit analysis and Net Present Value (NPV). While there are significant costs associated with the technology, the range of applications and benefits derived strengthen the case for its implementation.&lt;/Abstract>
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