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Monitoring and interpreting multistage and multicategory processes

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Text
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Title
Monitoring and interpreting multistage and multicategory processes
SubTitle
PartName
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NonSort
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ETD_1878
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051809
Language (objectPart = )
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eng
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theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Industrial and Systems Engineering
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Process control--Mathematical models
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Manufacturing processes--Quality control
Abstract
Consider processes where a transaction moves through stages and falls within a category at each stage. For example, in a tax complaint process, the stages are the steps taxpayers follow to resolve a property tax dispute from initial complaint through final resolution. The primary motivation here is customer service, although the transactions could be related to manufacturing applications as well.
The main contribution here is a method to monitor the fractions and numbers of transactions within and across stages of multistage and multicategory processes, a problem that has not been formulated before in the literature. The proposed method not only signals an out-of-control situation, it identifies accurately and easily which stages and categories are causing the disturbance, providing interpretations within and across stages of the process.
The proposed methodology works as follows: If a multinomial distribution fits the number of transactions in each category at every stage, then the process is decomposed into single stages that are monitored separately, and finally into independent binary substages with two categories. Each binary substage is characterized by a conditional probability and monitored with an independent fraction, called a tree fraction. The number of tree fractions that are monitored depends on the number of final categories, i.e., those that do not split in any further categories, not on the number of stages.
Two other contributions, summarized next, address the single stage case. Each is useful by itself, and each contributes to the method for the multistage case as well.
The first is a new two-sided CUSUM Arcsine method to monitor a process with two categories. The second is the p-tree method that monitors a multinomial process. The p-tree method not only signals an out-of-control situation, it identifies accurately which categories are causing the problem, in contrast to the widely used method in Marcucci (1985).
Future research would cover monitoring other types of multistage processes in service. An application of using probability trees to test and interpret associations in contingency tables is envisioned.
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electronic resource
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ix, 144 p. : ill.
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Ph.D.
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Includes bibliographical references (p. 114-120)
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by Rodrigo Ignacio Duran Lopez
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Duran Lopez
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Rodrigo Ignacio
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1963-
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author
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Rodrigo Ignacio Duran Lopez
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Albin
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Susan
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Susan L Albin
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Chaovalitwongse
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Wanpracha
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Advisory Committee
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Wanpracha Chaovalitwongse
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Lahr
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Michael
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outside member
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Michael L Lahr
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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2009
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2009-10
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xx
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Rutgers University Electronic Theses and Dissertations
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ETD
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Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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Identifier (type = doi)
doi:10.7282/T3251JCC
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work
Copyright
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Copyright protected
Notice
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Open
Reason
Permission or license
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Duran Lopez
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Rodrigo
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Rodrigo Duran Lopez
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Rutgers University. Graduate School - New Brunswick
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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