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Objective comparison of design of experiments strategies in design and observations in practice

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dc.contributor.advisor Christopher L. Magee. en_US
dc.contributor.author Freeman, Ion Chalmers, 1968- en_US
dc.contributor.other System Design and Management Program. en_US
dc.date.accessioned 2006-06-20T12:52:24Z
dc.date.available 2006-06-20T12:52:24Z
dc.date.copyright 2004 en_US
dc.date.issued 2004 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/33163
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2004. en_US
dc.description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. en_US
dc.description Includes bibliographical references (p. 146-149). en_US
dc.description.abstract Design of Experiments (DoE) strategies in robust engineering determine which prototypes and how many of each are created and tested. A better strategy is one that delivers a closer-to-optimal performance at a lower experimental cost. Prototype testers who may use statistical DoE, design-build-test, or one-at-a-time methods in a wide variety of industries were sought out and interviewed to examine the strategies used in practice and how they fit into a proposed five-layer process support model. From these interviews, we see that DoE are competently and widely practiced. Some improvements to the state of the practice may include: contracts to specify and reward quality engineering among suppliers to complex product systems and wider use in light of new computing power of system level mathematical models for experimentation on complex systems. This thesis also examines the relative value of strategies in a particular response surface using a software-based comparator. The data is modified to simulate data environments with other levels of repeatability and interactions, and the way that these variables effect the performance of strategies is examined. The concept of an optimal design of experiments strategy is developed by abstracting the characteristics of a generic strategy and letting it develop in a genetic algorithm in that comparator. The framework for the evaluation of DoE strategies is one significant output to come out of this work that may be of use in future research. Further, the particular abstraction chosen for DoE strategies is offered to other researchers as an exemplar of a particular perspective, to help engender dialogue about methods for optimizing prototype testing policy. en_US
dc.description.statementofresponsibility by Ion Chalmers Freeman. en_US
dc.format.extent 149 p. en_US
dc.format.extent 1152528 bytes
dc.format.extent 1152722 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject System Design and Management Program. en_US
dc.title Objective comparison of design of experiments strategies in design and observations in practice en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department System Design and Management Program. en_US
dc.identifier.oclc 57537076 en_US


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