Efficient Sampling Plans for Control Charts When Monitoring an Autocorrelated Process

dc.contributor.authorZhong, Xinen
dc.contributor.committeechairReynolds, Marion R. Jr.en
dc.contributor.committeememberVining, G. Geoffreyen
dc.contributor.committeememberWoodall, William H.en
dc.contributor.committeememberBirch, Jeffrey B.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T20:07:54Zen
dc.date.adate2006-03-15en
dc.date.available2014-03-14T20:07:54Zen
dc.date.issued2006-02-24en
dc.date.rdate2009-03-15en
dc.date.sdate2006-03-01en
dc.description.abstractThis dissertation investigates the effects of autocorrelation on the performances of various sampling plans for control charts in detecting special causes that may produce sustained or transient shifts in the process mean and/or variance. Observations from the process are modeled as a first-order autoregressive process plus a random error. Combinations of two Shewhart control charts and combinations of two exponentially weighted moving average (EWMA) control charts based on both the original observations and on the process residuals are considered. Three types of sampling plans are investigated: samples of n = 1, samples of n > 1 observations taken together at one sampling point, or samples of n > 1 observations taken at different times. In comparing these sampling plans it is assumed that the sampling rate in terms of the number of observations per unit time is fixed, so taking samples of n = 1 allows more frequent plotting. The best overall performance of sampling plans for control charts in detecting both sustained and transient shifts in the process is obtained by taking samples of n = 1 and using an EWMA chart combination with a observations chart for mean and a residuals chart for variance. The Shewhart chart combination with the best overall performance, though inferior to the EWMA chart combination, is based on samples of n > 1 taken at different times and with a observations chart for mean and a residuals chart for variance.en
dc.description.degreePh. D.en
dc.identifier.otheretd-03012006-103618en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-03012006-103618/en
dc.identifier.urihttp://hdl.handle.net/10919/26337en
dc.publisherVirginia Techen
dc.relation.haspartDissertation-XinZhong.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectdispersed samplingen
dc.subjectconcentrated samplingen
dc.subjectautocorrelationen
dc.subjectShewhart control charten
dc.subjectstatistical process controlen
dc.subjectexponentially weighted moving average control charen
dc.titleEfficient Sampling Plans for Control Charts When Monitoring an Autocorrelated Processen
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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