Reliability Analysis of Weibull Distribution under Unified Progressive Hybrid Censoring in Partially Accelerated Life Tests

Abstract

This study focuses on estimating reliability for the Weibull distribution within the framework of constant-stress partially accelerated life tests, incorporating the unified Type-I progressive hybrid censoring scheme that has not been previously examined. The unknown parameters of the Weibull model, including acceleration factors and key reliability measures such as the reliability function and hazard rate function under normal use conditions, are estimated. The maximum likelihood method is used to obtain point estimates and approximate confidence intervals. Additionally, a Bayesian approach based on Markov Chain Monte Carlo sampling is applied to compute point estimates and Bayesian credible intervals, assuming a squared error loss function. A simulation study is conducted to compare the performance of the estimators using criteria such as mean squared error, interval width, and coverage probability. Finally, two real-world data sets from accelerated life testing are analyzed to illustrate the practical usefulness of the proposed methods.