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MODELING AND CHARACTERIZATIONS OF NEW NOTIONS IN LIFE TESTING WITH STATISTICAL APPLICATIONS
Title
MODELING AND CHARACTERIZATIONS OF NEW NOTIONS IN LIFE TESTING WITH STATISTICAL APPLICATIONS.
Creator
Sepehrifar, Mohammad, Ahmad, Ibrahim, University of Central Florida
Abstract / Description
Knowing the class to which a life distribution belongs gives us an idea about the aging of the device or system the life distribution represents, and enables us to compare the aging properties of different systems. This research intends to establish several new nonparametric classes of life distributions defined by the concept of inactivity time of a unit with a guaranteed minimum life length. These classes play an important role in the study of reliability theory, survival analysis,...
Show moreKnowing the class to which a life distribution belongs gives us an idea about the aging of the device or system the life distribution represents, and enables us to compare the aging properties of different systems. This research intends to establish several new nonparametric classes of life distributions defined by the concept of inactivity time of a unit with a guaranteed minimum life length. These classes play an important role in the study of reliability theory, survival analysis, maintenance policies, economics, actuarial sciences and many other applied areas.
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Date Issued
2006
Identifier
CFE0001316, ucf:47030
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001316
ACCELERATED LIFE TESTING OF SUBSEA EQUIPMENT UNDER HYDROSTATIC PRESSURE
Title
ACCELERATED LIFE TESTING OF SUBSEA EQUIPMENT UNDER HYDROSTATIC PRESSURE.
Creator
Thiraviam, Amar Raja, Malone, Linda, University of Central Florida
Abstract / Description
Accelerated Life Testing (ALT) is an effective method of demonstrating and improving product reliability in applications where the products are expected to perform for a long period of time. ALT accelerates a given failure mode by testing at amplified stress level(s) in excess of operational limits. Statistical analysis (parameter estimation) is then performed on the data, based on an acceleration model to make life predictions at use level. The acceleration model thus forms the basis of...
Show moreAccelerated Life Testing (ALT) is an effective method of demonstrating and improving product reliability in applications where the products are expected to perform for a long period of time. ALT accelerates a given failure mode by testing at amplified stress level(s) in excess of operational limits. Statistical analysis (parameter estimation) is then performed on the data, based on an acceleration model to make life predictions at use level. The acceleration model thus forms the basis of accelerated life testing methodology. Well established accelerated models such as the Arrhenius model and the Inverse Power Law (IPL) model exist for key stresses such as temperature and voltage. But there are other stresses like subsea pressure, where there is no clear model of choice. This research proposes a pressure-life (acceleration) model for the first time for life prediction under subsea pressure for key mechanical/physical failure mechanisms. Three independent accelerated tests were conducted and their results analyzed to identify the best model for the pressure-life relationship. The testing included material tests in standard coupons to investigate the effect of subsea pressure on key physical, mechanical, and electrical properties. Tests were also conducted at the component level on critical components that function as a pressure barrier. By comparing the likelihood values of multiple reasonable candidate models for the individual tests, the exponential model was identified as a good model for the pressure-life relationship. In addition to consistently providing good fit among the three tests, the exponential model was also consistent with field data (validation with over 10 years of field data) and demonstrated several characteristics that enable robust life predictions in a variety of scenarios. In addition the research also used the process of Bayesian analysis to incorporate prior information from field and test data to bolster the results and increase the confidence in the predictions from the proposed model.
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Date Issued
2010
Identifier
CFE0003411, ucf:48422
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003411