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In this paper, we have investigated the reliability of a K-out-of-N systemfor the components following Weibull distribution based on the generalizedprogressive hybrid censored data. We have obtained the maximum likelihoodestimates (MLEs) of the unknown parameters and the reliability function of thesystem. Using asymptotic normality property of MLEs, the correspondingasymptotic confidence intervals are constructed. Furthermore, Bayes estimatesare derived under squared error loss function with informative prior by usingMarkov Chain Monte Carlo (MCMC) technique. Highest posterior density (HPD)credible intervals are obtained. A Monte Carlo simulation study is carried outto compare performance of the established estimates. Finally, a real data setis considered for illustrative purposes.

Reliability analysis of K-out-of-N system for Weibull components based on generalized progressive hybrid censored data