<?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>2026-09-18T21:33:08Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/17816" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/17816</identifier><datestamp>2022-01-13T07:54:11Z</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">Olivier L. de Weck.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Schuman, Todd, 1979-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Aeronautics and Astronautics</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2005-06-02T18:47:13Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2005-06-02T18:47:13Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2004</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2004</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">56558145</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 120-123).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The introduction of concurrent design practices to the aerospace industry has greatly increased the efficiency and productivity of engineers during design sessions. Teams that are well-versed in such practices such as JPL's Team X are able to thoroughly examine a trade space and develop a family of reliable point designs for a given mission in a matter of weeks compared to the months or years sometimes needed for traditional design. Simultaneously, advances in computing power have given rise to a host of potent numerical optimization methods capable of solving complex multidisciplinary optimization problems containing hundreds of variables, constraints, and governing equations. Unfortunately, such methods are tedious to set up and require significant amounts of time and processor power to execute, thus making them unsuitable for rapid concurrent engineering use. In some ways concurrent engineering and automated system-level optimization are often viewed as being mutually incompatible. It is therefore desirable to devise a system to allow concurrent engineering teams to take advantage of these powerful techniques without hindering the teams' performance. This paper proposes such an integration by using parametric approximations of the subsystem models. These approximations are then linked to a system-level optimizer that is capable of reaching a solution more quickly than normally possible due to the reduced complexity of the approximations. The integration structure is described in detail and applied to a standard problem in aerospace engineering. Further, a comparison is made between this application and traditional concurrent engineering through an experimental trial with two groups each using a different method to</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">(cont.) solve the standard problem. Each method is evaluated in terms of optimizer accuracy, time to solution, and ease of use. The results suggest that system-level optimization, running as a background process during integrated concurrent engineering, is potentially advantageous as long as it is judiciously implemented from a mathematical and organizational perspective.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Todd Schuman.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">123 p.</dim:field>
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   <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">Aeronautics and Astronautics.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Integration of system-level optimization with concurrent engineering using parametric subsystem modeling</dim:field>
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   	&lt;Title>Integration of system-level optimization with concurrent engineering using parametric subsystem modeling&lt;/Title>
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   	&lt;PublicationDate>2004&lt;/PublicationDate>
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    &lt;Keyword>Aeronautics and Astronautics.&lt;/Keyword>
   	&lt;Abstract>The introduction of concurrent design practices to the aerospace industry has greatly increased the efficiency and productivity of engineers during design sessions. Teams that are well-versed in such practices such as JPL&amp;apos;s Team X are able to thoroughly examine a trade space and develop a family of reliable point designs for a given mission in a matter of weeks compared to the months or years sometimes needed for traditional design. Simultaneously, advances in computing power have given rise to a host of potent numerical optimization methods capable of solving complex multidisciplinary optimization problems containing hundreds of variables, constraints, and governing equations. Unfortunately, such methods are tedious to set up and require significant amounts of time and processor power to execute, thus making them unsuitable for rapid concurrent engineering use. In some ways concurrent engineering and automated system-level optimization are often viewed as being mutually incompatible. It is therefore desirable to devise a system to allow concurrent engineering teams to take advantage of these powerful techniques without hindering the teams&amp;apos; performance. This paper proposes such an integration by using parametric approximations of the subsystem models. These approximations are then linked to a system-level optimizer that is capable of reaching a solution more quickly than normally possible due to the reduced complexity of the approximations. The integration structure is described in detail and applied to a standard problem in aerospace engineering. Further, a comparison is made between this application and traditional concurrent engineering through an experimental trial with two groups each using a different method to&lt;/Abstract>
   	&lt;Abstract>(cont.) solve the standard problem. Each method is evaluated in terms of optimizer accuracy, time to solution, and ease of use. The results suggest that system-level optimization, running as a background process during integrated concurrent engineering, is potentially advantageous as long as it is judiciously implemented from a mathematical and organizational perspective.&lt;/Abstract>
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