Abstract/Details

Contributions to accelerated destructive degradation test planning


2010 2010

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Abstract (summary)

Many failure mechanisms can be traced to underlying degradation processes. Degradation eventually leads to a weakness that can cause a failure for products. When it is possible to measure degradation, such data often provide more information than traditional failure-time data for purposes of assessing and improving product reliability. For some products, however, degradation rates at use conditions are so low that appreciable degradation will not be observed in a test of practical time length. In such cases, it might be possible to use some accelerating variables (e.g., temperature, voltage, or pressure) to accelerate the degradation processes. In today’s manufacturing industries, accelerated destructive degradation tests (ADDTs) are widely used to obtain timely product reliability information. In designing an experiment, decisions must be made before data collection, and data collection is usually restricted by limited resources. Careful test planning is crucial for efficient use of limited resources: test time, test units, and test facilities. The basic goal in designing an experiment is to improve the statistical inference for the quantities of interest by selecting appropriate test conditions to minimize or control the variability of the estimator of interest. Generally, an ADDT plan specifies a set of testing conditions and the corresponding allocations of test units to each condition. In this dissertation, we study the test planning methods for designing accelerated destructive degradation tests from three aspects, including non-Bayesian and Bayesian methods. First, Chapter 2 presents the non-Bayesian methods for accelerated destructive degradation test planning when there is only one failure cause for the testing products. Second, Chapter 3 describes the non-Bayesian methods for accelerated destructive degradation test planning when more than one failure cause (sometimes known as competing risks) are induced for the produces which are tested at high-stress levels of accelerating variables. Third, Chapter 4 shows the Bayesian methods for accelerated destructive degradation test planning.

Indexing (details)


Subject
Statistics;
Industrial engineering
Classification
0463: Statistics
0546: Industrial engineering
Identifier / keyword
Applied sciences; Pure sciences; Accelerated degradation; Destructive degradation; Product reliability; Test planning
Title
Contributions to accelerated destructive degradation test planning
Author
Shi, Ying
Number of pages
90
Publication year
2010
Degree date
2010
School code
0097
Source
DAI-B 72/03, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781124430249
Advisor
Meeker, William Q.
Committee member
Jackman, John K.; Liu, Peng; Marasinghe, Mervyn G.; Wu, Huaiqing
University/institution
Iowa State University
Department
Statistics
University location
United States -- Iowa
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3438733
ProQuest document ID
848502793
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/848502793
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