Statistical Methods for Reliability Data from Designed Experiments

dc.contributor.authorFreeman, Laura J.en
dc.contributor.committeechairVining, G. Geoffreyen
dc.contributor.committeememberHong, Yilien
dc.contributor.committeememberKowalski, Scott M.en
dc.contributor.committeememberDu, Pangen
dc.contributor.committeememberBirch, Jeffrey B.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T21:10:49Zen
dc.date.adate2010-05-07en
dc.date.available2014-03-14T21:10:49Zen
dc.date.issued2010-05-06en
dc.date.rdate2010-05-07en
dc.date.sdate2010-05-07en
dc.description.abstractProduct reliability is an important characteristic for all manufacturers, engineers and consumers. Industrial statisticians have been planning experiments for years to improve product quality and reliability. However, rarely do experts in the field of reliability have expertise in design of experiments (DOE) and the implications that experimental protocol have on data analysis. Additionally, statisticians who focus on DOE rarely work with reliability data. As a result, analysis methods for lifetime data for experimental designs that are more complex than a completely randomized design are extremely limited. This dissertation provides two new analysis methods for reliability data from life tests. We focus on data from a sub-sampling experimental design. The new analysis methods are illustrated on a popular reliability data set, which contains sub-sampling. Monte Carlo simulation studies evaluate the capabilities of the new modeling methods. Additionally, Monte Carlo simulation studies highlight the principles of experimental design in a reliability context. The dissertation provides multiple methods for statistical inference for the new analysis methods. Finally, implications for the reliability field are discussed, especially in future applications of the new analysis methods.en
dc.description.degreePh. D.en
dc.identifier.otheretd-05072010-102728en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05072010-102728/en
dc.identifier.urihttp://hdl.handle.net/10919/37729en
dc.publisherVirginia Techen
dc.relation.haspartFreeman_LauraJ_D_2010.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectRandom Effecten
dc.subjectNonlinear Mixed Modelsen
dc.subjectLifetime Dataen
dc.subjectDesign of Experimentsen
dc.subjectWeibull Distributionen
dc.subjectWeighted Least Squaresen
dc.titleStatistical Methods for Reliability Data from Designed Experimentsen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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