Optimal and Robust Designs of Step-stress Accelerated Life Testing Experiments for Proportional Hazards Models

摘要

Accelerated life testing (ALT) is widely used to obtain reliability information about a product within alimited time frame. The Cox s proportional hazards (PH) model is often utilized for reliability prediction.My master thesis research focuses on designing accelerated life testing experiments for reliability estimation.We consider multiple step-stress ALT plans with censoring. The optimal stress levels and times of changingthe stress levels are investigated. We discuss the optimal designs under three optimality criteria. They areD-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed iscorrect. Due to the nature of prediction made from ALT experimental data, attained under the stress levelshigher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot betested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robustdesigns is also explored.