Abstract
The accelerated life tests provide quick information on the life time distributions by testing materials or products at higher than basic conditional levels of stress such as pressure, high temperature, vibration, voltage or load to induce failures. In this paper, the acceleration model assumed is log linear model. Constant stress tests are discussed based on Type I and Type II censoring. The Kumaraswmay Weibull distribution is used. The estimators of the parameters, reliability, hazard rate functions and p-th percentile at normal condition, low stress, and high stress are obtained. In addition, credible intervals for parameters of the models are constructed. Optimum test plan are designed. Some numerical studies are used to solve the complicated integrals such as Laplace and Markov Chain Monte Carlo methods.
Highlights
Technology advancements are continuously increasing the improvements in manufacturing designs
ER1 is better than ER2 for all sample sizes
The two-sided 95% credible intervals for the parameters of KumW are displayed in Tables 2 and 5
Summary
Technology advancements are continuously increasing the improvements in manufacturing designs. It becomes more difficult to obtain information about lifetime of materials or products or with high reliability at the testing time of that device under normal conditions. Accelerated life tests (ALTs) are often used in such problems in order to shorten the life of test items This test provides information quickly on the life distribution of the products or materials by testing them at higher than normal levels of stress such as voltage, high temperature, pressure, load or vibration to stimulate early failures. The Kumaraswamy Weibull (KumW) is a quite flexible model in analyzing positive data It contains special cases like the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and the new Kumaraswamy exponential distribution. These shape parameters allow a high degree of flexibility of the KumW distribution It attracts wider applications in engineering, reliability and in other research areas.
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