Reliability Analysis of Multicomponent Stress–Strength Systems Under Progressive First‐Failure Censoring Using the Exponentiated Half‐Logistic Distribution

ABSTRACT This paper develops a comprehensive reliability framework for multicomponent stress–strength systems, where both strength and stress variables follow the exponentiated half‐logistic (EHL) distribution. Reliability analysis is performed under progressive first‐failure censoring, a flexible and practically relevant censoring scheme for modern life testing. A closed‐form expression is derived for the multicomponent reliability function , representing the probability that at least out of strength units bear a common stress. Parameter estimation is addressed within both frequentist and Bayesian paradigms. MLEs with asymptotic and bootstrap confidence intervals are derived, while Bayesian inference is carried out under the GELF using Lindley approximation and the Markov chain Monte Carlo (MCMC) techniques, with the corresponding CrIs. The efficiency and robustness of the proposed procedures are examined through extensive Monte Carlo simulations under various censoring schemes. Two real datasets, concerning software reliability and carbon‐fibers strength, are analyzed to demonstrate the practical relevance of the model. The results establish the EHL distribution as a flexible and effective tool for modeling reliability in engineering and industrial systems, thereby extending methodological and applied insights in stochastic reliability analysis.