Quality measurement plan using Monte Carlo methods

buir.advisorGürler, Ülkü
dc.contributor.authorZouaoui, Faker
dc.date.accessioned2016-01-08T20:14:53Z
dc.date.available2016-01-08T20:14:53Z
dc.date.issued1997
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionAnkara : Department of Industrial Engineerering and Institute of Engineering and Sciences, Bilkent Univ., 1997.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1997.en_US
dc.descriptionIncludes bibliographical references leaves 59-63en_US
dc.description.abstractThis study considers the Quality Measurement Plan (QMP), a system implemented for reporting the quality assurance audit results to Bell system management. QMP is derived from a new Bayesian approach to the empirical Bayes problem for Poisson observations. It uses both the current and past data to compute estimates for the quality of the current production. The QMP estimator developed by Hoadley in 1981 is based on many complicated approximations. Sampling approaches such as the Gibbs sampler and Importance-sampling are alternative techniques that avoid these approximations and permit the computation of the quality estimates through Monte Carlo methods. Here we discuss the approaches and the algorithms for implementing some Monte Carlo-based approaches on the QMP model. We also show via simulation that although the QMP algorithm can be computationally more convenient, the sampling approaches mentioned above give more accurate estimates of current quality.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityZouaoui, Fakeren_US
dc.format.extentxi, 63 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/17954
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectQMPen_US
dc.subjectSubstitution-Samplingen_US
dc.subjectImportance-Samplingen_US
dc.subjectGibbs Sampleren_US
dc.subjectHierarchical Bayesen_US
dc.subject.lccQA298 .Z68 1997en_US
dc.subject.lcshMonte Carlo method.en_US
dc.titleQuality measurement plan using Monte Carlo methodsen_US
dc.typeThesisen_US

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