Estimating the Generalized Exponential Distribution Parameters and the Acceleration Factor under Constant-Stress Partially Accelerated Life Testing with Type-II Censoring
Accelerated life testing (ALT) and partially accelerated life testing (PALT) are frequently used in modern reliability engineering. ALT and PALT are run to obtain information on the life of the products and materials in a shorter time and at lower cost. The experimental units are subject to st...
Збережено в:
| Дата: | 2013 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Інститут проблем міцності ім. Г.С. Писаренко НАН України
2013
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| Назва видання: | Проблемы прочности |
| Теми: | |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/112673 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | Estimating the Generalized Exponential Distribution Parameters and the Acceleration Factor under Constant-Stress Partially Accelerated Life Testing with Type-II Censoring / A.A. Ismail // Проблемы прочности. — 2013. — № 6. — С. 82-94. — Бібліогр.: 19 назв. — англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Резюме: | Accelerated life testing (ALT) and partially accelerated
life testing (PALT) are frequently used
in modern reliability engineering. ALT and
PALT are run to obtain information on the life
of the products and materials in a shorter time
and at lower cost. The experimental units are
subject to stress conditions that are more severe
than those encountered in normal use condition
to induce early failures. ALT or PALT can be
carried out using constant, step, progressive, cyclic
and random stress loadings. This paper considers
the problem of estimating the generalized
exponential (GE) distribution parameters and
the acceleration factor under constant-stress
PALT model. The main objective is to derive the
maximum likelihood estimators (MLEs) of the
parameters of the GE distribution and the acceleration
factor when the data are type-II censored
from constant-stress PALT. Also, the performance
of the MLEs is investigated numerically
for different sample sizes and different parameter
values using the mean square error. In addition,
the approximate confidence intervals of the
model parameters are constructed. Moreover,
the likelihood ratio bounds (LRB) method is
used to obtain confidence bounds of the model
parameters when the sample size is small. For
illustration, a simulation study is conducted. It
is observed that the simulation results support
the theoretical findings. |
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