Statistical Process Control (SPC) is a statistical method for monitoring variability of processes. Process variation can be categorized as common cause and special cause. Common causes are the natural or expected variation of some change in the process. The presence of a special cause indicates that the process is not in a state of statistical control. The SPC methodology dictates that a search should be initiated when a special cause is detected. This thesis is about the set-up of magnitude robust control chart and CUSUM charts for detecting changes in Weibull processes. The research includes the comparison of the ARL performance of the control charts. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in
partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Spring Semester, 2009. / Date of Defense: October 31, 2008. / Statistical Process Control, Weibull Distribution, Magnitude Robust Control Chart, CUSUM Chart, ARL, Maximum Likelihood Estimates, Maximum Likelihood Ratio Test / Includes bibliographical references. / Joseph J. Pignatiello, Jr., Professor Directing Thesis; Samuel A. Awoniyi, Committee Member; Arda Vanli, Committee Member; Okenwa Okoli, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_168687 |
| Contributors | Zhang, Mang (authoraut), Pignatiello, Joseph J. (professor directing thesis), Awoniyi, Samuel A. (committee member), Vanli, Arda (committee member), Okoli, Okenwa (committee member), Department of Industrial and Manufacturing Engineering (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
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