Bayesian Analysis for Burr-XII Masked System in Step-Stress Partially Accelerated Life Test Under Type-I Progressive Hybrid Censoring

Abstract

This paper discusses the reliability analysis for a series system in step-stress partially accelerated lifetime test under Type-I progressive hybrid censoring, where independent Burr-XII distributed lifetimes are assumed for the components. In many cases, the exact component causing the system failure cannot be identified and the cause of failure is masked. Bayesian approach combined with auxiliary variables is applied for estimating the parameters of the model when the masking probability is dependent on the component. Further, the reliability and hazard rate functions of the system and components are estimated under use stress level. Simulation studies are performed to demonstrate the efficiency of the methods proposed in this paper under different masking probabilities and different progressive removal schemes.