Statistical Analysis of Inverse Weibull Constant-Stress Partially Accelerated Life Tests with Adaptive Progressively Type I Censored Data

In life-testing investigations, accelerated life testing is crucial since it reduces both time and costs. this study, constant-stress partially tests using adaptive progressively Type I censored samples are taken into account. This accomplished under the assumption that lifespan of products normal use conditions follows inverse Weibull distribution. addition to maximum likelihood approach, product spacing procedure utilized obtain point interval estimates model parameters as well acceleration factor. Employing premise independent gamma priors, Bayes squared error loss function credible intervals obtained based on functions via Markov chain Monte Carlo technique. To assess effectiveness various approaches, a simulation study used because not possible compare findings theoretically. demonstrate applicability two real datasets for lifetime micro-droplets in ambient environment light-emitting diode failure data investigated. Based numerical results, estimate factor distribution suggested scheme with tests, recommended utilize Bayesian estimation approach.