<?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>2026-09-18T21:45:49Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/39688" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/39688</identifier><datestamp>2022-01-28T21:08:44Z</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">Donald B. Rosenfield and Daniel E. Whitney.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Vacha, Robin L. (Robin Lee)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Leaders for Manufacturing Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Leaders for Manufacturing Program at MIT</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="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2007-12-07T16:07:17Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2007-12-07T16:07:17Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2007</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2007</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/39688</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">175305087</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 77-78).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The production of aerospace grade titanium alloys is concentrated in a relatively small number of producers. The market for these materials has always been cyclical in nature. During periods of high demand, metal producers claim to operate near full capacity utilization. During periods of reduced demand, metal producers struggle to remain profitable. Additionally, the manufacturing processes for aerospace grade titanium alloys are capital intensive and require long lead-times in order to bring new capacity online. The combination of these factors often results in an inflexible titanium alloy raw material supply chain for Pratt &amp; Whitney. At the same time, Pratt &amp; Whitney experiences a variety of rare but disruptive events within the supply chain that affect their raw material requirements. Examples of these disruptive events include customer drop-in orders, manufacturing complications resulting in scrapped material, and planning deficiencies. In order to protect engine and spare part customers from delayed deliveries due to long lead-time raw materials, Pratt &amp; Whitney holds a strategic inventory of various titanium alloy raw material.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">(cont.) This thesis presents a mathematical model utilizing a Compound Poisson Process that can be used to optimize the amount of strategic titanium alloy raw material held by Pratt &amp; Whitney. The associated mathematical algorithms were programmed into Microsoft Excel creating the Strategic Raw Material Inventory Calculator. Historical data was then collected and used with this unique tool to calculate service levels at current inventory levels as well as optimized inventory levels under various scenarios.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Robin L. Vacha, Jr.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.B.A.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">85 p.</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">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Mechanical Engineering.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Leaders for Manufacturing Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Strategic raw material inventory optimization</dim:field>
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   	&lt;Title>Strategic raw material inventory optimization&lt;/Title>
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   	&lt;PublicationDate>2007&lt;/PublicationDate>
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        	&lt;DisplayName>Vacha, Robin L. (Robin Lee)&lt;/DisplayName>
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    &lt;Keyword>Sloan School of Management.&lt;/Keyword>
    &lt;Keyword>Mechanical Engineering.&lt;/Keyword>
    &lt;Keyword>Leaders for Manufacturing Program.&lt;/Keyword>
   	&lt;Abstract>The production of aerospace grade titanium alloys is concentrated in a relatively small number of producers. The market for these materials has always been cyclical in nature. During periods of high demand, metal producers claim to operate near full capacity utilization. During periods of reduced demand, metal producers struggle to remain profitable. Additionally, the manufacturing processes for aerospace grade titanium alloys are capital intensive and require long lead-times in order to bring new capacity online. The combination of these factors often results in an inflexible titanium alloy raw material supply chain for Pratt &amp;amp; Whitney. At the same time, Pratt &amp;amp; Whitney experiences a variety of rare but disruptive events within the supply chain that affect their raw material requirements. Examples of these disruptive events include customer drop-in orders, manufacturing complications resulting in scrapped material, and planning deficiencies. In order to protect engine and spare part customers from delayed deliveries due to long lead-time raw materials, Pratt &amp;amp; Whitney holds a strategic inventory of various titanium alloy raw material.&lt;/Abstract>
   	&lt;Abstract>(cont.) This thesis presents a mathematical model utilizing a Compound Poisson Process that can be used to optimize the amount of strategic titanium alloy raw material held by Pratt &amp;amp; Whitney. The associated mathematical algorithms were programmed into Microsoft Excel creating the Strategic Raw Material Inventory Calculator. Historical data was then collected and used with this unique tool to calculate service levels at current inventory levels as well as optimized inventory levels under various scenarios.&lt;/Abstract>
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