PROJECT TITLE :

Bayesian Analysis of a Simple Step-Stress Model Under Weibull Lifetimes

ABSTRACT:

The step-stress model is becoming quite in style for analyzing lifetime knowledge obtained from accelerated life testing experiments. In the usual step-stress experiment, stress levels are allowed to change at each step to urge fast failure of the experimental units. The simple step-stress model underneath totally different censoring schemes based mostly on Weibull lifetimes is considered during this paper. It's assumed that the lifetime distributions of the experimental units have totally different scale parameters at completely different stress levels, but they have the same shape parameter. Moreover, it is assumed that the lifetimes follow the Khamis-Higgins model. It is additional assumed that, as the strain level will increase, the scale parameter also will increase. We have a tendency to give Bayesian inference of the unknown parameters of the Weibull distribution underneath this order restriction on the size parameters. Monte Carlo simulations are performed to see the effectiveness of the proposed methodology, and a knowledge set has been analyzed for illustrative purposes.


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