This manuscript presents the concept of a novel multicomponent reliability function, \(\rho_{k} \left( t \right)\) . We have established estimation methodologies for this function utilizing progressive type II censoring, which subsequently facilitate the development of estimation techniques for multicomponent stress-strength reliability function, \(\rho_{s, \, k}\) . The system under consideration comprises k strength components that are statistically independent and identically distributed, wherein each strength component experiences a common random stress. We consider independent stress and strength components which adhere to distinct unit generalized exponential distributions. We employ classical and Bayesian techniques for estimating the reliability functions, \(\rho_{k} \left( t \right)\) and \(\rho_{s, \, k}\) . To assess the performance of the proposed estimators, we make use of mean squared errors obtained utilizing Monte Carlo simulation technique. Finally, we provide two illustrative examples to demonstrate the application of our findings.
