A response surface approach to data analysis in robust parameter design

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dc.contributor.authorKim, Yoon G.en
dc.contributor.committeechairMyers, Raymond H.en
dc.contributor.committeememberHinkelmann, Klaus H.en
dc.contributor.committeememberHoltzman, Golde I.en
dc.contributor.committeememberKrutchkoff, Richard G.en
dc.contributor.committeememberPirie, Walter R.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T21:15:05Zen
dc.date.adate2006-06-19en
dc.date.available2014-03-14T21:15:05Zen
dc.date.issued1992-09-15en
dc.date.rdate2006-06-19en
dc.date.sdate2006-06-19en
dc.description.abstractIt has become obvious that combined arrays and a response surface approach can be effective tools in our quest to reduce (process) variability. An important aspect of the improvement of quality is to suppress the magnitude of the influence coming from subtle changes of noise factors. To model and control process variability induced by noise factors we take a response surface approach. The derivative of the standard response function with respect to noise factors, i. e., the slopes of the response function in the direction of the noise factors, play an important role in the study of the minimum process variance. For better understanding of the process variability, we study various properties of both biased and the unbiased estimators of the process variance. Response surface modeling techniques and the ideas involved with variance modeling and estimation through the function of the aforementioned derivatives is a valuable concept in this study. In what follows, we describe the use of the response surface methodology for situations in which noise factors are used. The approach is to combine Taguchi's notion of heterogeneous variability with standard design and modeling techniques available in response surface methodology.en
dc.description.degreePh. D.en
dc.format.extentvi, 115 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-06192006-125721en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06192006-125721/en
dc.identifier.urihttp://hdl.handle.net/10919/38627en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V856_1992.K5595.pdfen
dc.relation.isformatofOCLC# 27408244en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V856 1992.K5595en
dc.subject.lcshRobust statisticsen
dc.titleA response surface approach to data analysis in robust parameter designen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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