Poisson count process are often used to model the number of occurrences over some interval unit. In an industrial quality control setting, these processes are often used to model the number of nonconformities per unit of product. Current methods used for monitoring and estimating changes in Poisson count processes assume that the magnitude and type of change are known a priori. Since rarely in practice are these known, this dissertation reports on the development and evaluation of several methods for detecting and estimating change points when the magnitude and type of change are unknown. Instead, the only assumption requires that the type of change belongs to a family of monotonic change types. Results indicate that the methodologies proposed throughout this dissertation research provide robust detection and estimation capabilities (relative to current methods) with regard to the magnitude and type of monotonic change that may be present. / A Dissertation Submitted to the Department of Industrial Engineering in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Summer Semester, 2004. / May 28, 2004. / Maximum Likelihood Estimation, Hypothesis Testing, Quality Control, Special Cause Identification, Statistical Process Control, Poisson Count Processes, Process Improvement, Change Point Estimation, Likelihood Ratio, Change Point Detection, Average Run Length, Order-Restricted Inference, CUSUM Control Chart, PAV Algorithm / Includes bibliographical references. / Joseph J. Pignatiello, Jr., Professor Directing Dissertation; Anuj Srivastava, Outside Committee Member; James R. Simpson, Committee Member; Chuck Zhang, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_180264 |
| Contributors | Perry, Marcus B. (authoraut), Pignatiello, Joseph J. (professor directing dissertation), Srivastava, Anuj (outside committee member), Simpson, James R. (committee member), Zhang, Chuck (committee member), Department of Industrial and Manufacturing Engineering (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
Page generated in 0.0213 seconds