<?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>2026-09-18T22:03:48Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/101528" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/101528</identifier><datestamp>2026-06-06T01:04:06Z</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 and Duane S. Boning.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Zhang, Shaozheng, M. Eng Massachusetts Institute of Technology</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">2016-03-03T21:06:53Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2016-03-03T21:06:53Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/101528</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">939919071</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng. in Manufacturing, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015.</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 80-81).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The purpose of this project is to set up a statistical process control (SPC) system in a high volume machining center to reduce the scrap rate and improve the manufacturing quality. The system is demonstrated on a machining center at Waters Corporation as part of a team internship project. This thesis focuses on the gage repeatability and reproducibility study (Gage R&amp;R study) for the implementation of the SPC system. Based on the knowledge about the machining processes and the gages available, we select the proper gages for different dimensions to conduct the Gage R&amp;R study. Gage capabilities are analyzed and root-cause analysis for incapable gages is performed. Related reaction plans are developed and implemented in order to improve the gage capabilities. Discussion about tolerance redesign leads to the adjustment of specifications in the manufacturing area. As a result of these efforts, we find that the existing measurement system is capable for the SPC real time inspection system. As for the final result for this entire project, we demonstrated that with the SPC system, we successfully reduce the scrap rate by half and thus offer substantial cost savings as well as improved product quality.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Shaozheng Zhang.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng. in Manufacturing</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">81 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">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" 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">Statistical process control (SPC) in a high volume machining center : gage repeatability and reproducibility study</dim:field>
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   	&lt;Title>Statistical process control (SPC) in a high volume machining center : gage repeatability and reproducibility study&lt;/Title>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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        	&lt;DisplayName>Zhang, Shaozheng, M. Eng Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;Keyword>Mechanical Engineering.&lt;/Keyword>
   	&lt;Abstract>The purpose of this project is to set up a statistical process control (SPC) system in a high volume machining center to reduce the scrap rate and improve the manufacturing quality. The system is demonstrated on a machining center at Waters Corporation as part of a team internship project. This thesis focuses on the gage repeatability and reproducibility study (Gage R&amp;amp;R study) for the implementation of the SPC system. Based on the knowledge about the machining processes and the gages available, we select the proper gages for different dimensions to conduct the Gage R&amp;amp;R study. Gage capabilities are analyzed and root-cause analysis for incapable gages is performed. Related reaction plans are developed and implemented in order to improve the gage capabilities. Discussion about tolerance redesign leads to the adjustment of specifications in the manufacturing area. As a result of these efforts, we find that the existing measurement system is capable for the SPC real time inspection system. As for the final result for this entire project, we demonstrated that with the SPC system, we successfully reduce the scrap rate by half and thus offer substantial cost savings as well as improved product quality.&lt;/Abstract>
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