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Modeling and planning accelerated life testing with proportional odds

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TitleInfo
Title
Modeling and planning accelerated life testing with proportional odds
Name (type = personal)
NamePart (type = family)
Zhang
NamePart (type = given)
Hao
DisplayForm
Hao Zhang
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
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Elsayed
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Elsayed
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Advisory Committee
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Elsayed Elsayed
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chair
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Coit
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David
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Advisory Committee
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David Coit
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RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Pham
NamePart (type = given)
Hoang
Affiliation
Advisory Committee
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Hoang Pham
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internal member
Name (type = personal)
NamePart (type = family)
Kolassa
NamePart (type = given)
John
Affiliation
Advisory Committee
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John Kolassa
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outside member
Name (type = personal)
NamePart (type = family)
Tortorella
NamePart (type = given)
Michael
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Advisory Committee
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Michael Tortorella
Role
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outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School-New Brunswick
Role
RoleTerm (authority = RULIB)
school
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Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2007
DateOther (qualifier = exact); (type = degree)
2007
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
PhysicalDescription
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electronic
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application/pdf
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text/xml
Extent
xiii, 182 pages
Abstract (type = abstract)
Accelerated life testing (ALT) is a method for estimating the reliability of products at normal operating conditions from the failure data obtained at the severe conditions. We propose an ALT model based on the proportional odds (PO) assumption to analyze failure time data and investigate the optimum ALT plans for multiple-stress-type cases based on the PO assumption.
We present the PO-based ALT model and propose the parameter estimation procedures by approximating the general baseline odds function with a polynomial function.
Numerical examples with experimental data and Monte Carlo simulation data verify that the PO-based ALT model provides more accurate reliability estimate for the failure time data exhibiting PO properties.
The accuracy of the reliability estimates is directly affected by the reliability inference model and how the ALT is conducted. The latter is addressed in the literature as the design of ALT test plans. Design of ALT test plans under one type of stress may mask the effect of other critical types of stresses that could lead to the component's failure.
The extended life of today's products makes it difficult to obtain "enough" failures in a reasonable amount of testing time using single stress type. Therefore, it is more realistic to consider multiple stress types. This is the first research that investigates the design of optimum ALT test plans with multiple stress types. We formulate nonlinear optimization problems to determine the optimum ALT plans. The optimization problem was solved with a numerical optimization method.
Reliability practitioners could choose different ALT plans in terms of the stress loading types. In this dissertation we conduct the first investigation of the equivalency of ALT plans, which enables reliability practitioners to choose the appropriate ALT plan according to resource restrictions. The results of this research show that one can indeed develop efficient test plans that can provide accurate reliability estimate at design conditions in much shorter test duration than the traditional test plans.
Finally, we conduct experimental testing using miniature light bulbs. The test units are subjected to different stress types. The results validate the applicability of the PO-based ALT models.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references (p. 171-179).
Subject (authority = RUETD)
Topic
Industrial and Systems Engineering
Subject (authority = ETD-LCSH)
Topic
Accelerated life testing
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.13840
Identifier (type = FEDORA_PID)
rutgers-lib:21342
Identifier
ETD_161
Identifier (type = doi)
doi:10.7282/T3P55P06
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
Copyright
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Availability
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Open
AssociatedEntity (AUTHORITY = rulib); (ID = 1)
Name
Hao Zhang
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Copyright holder
Affiliation
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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