Inference for Step-Stress Models

• Activity Number: 298
• Type: Topic Contributed
• Date/Time: Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Nandini Kannan*
• Companies: National Science Foundation

Abstract

In life-testing experiments, researchers are often interested in the effects of different risk factors such as temperature, voltage, and dose on the lifetimes of experimental units. Accelerated testing allows the experimenter to increase the levels of the stress factors resulting in shorter failure times than would be observed under normal operating conditions. A special class of accelerated tests is the class of step-stress tests which allows the experimenter to increase the stress levels at fixed times during the experiment.

In this talk, we describe the Cumulative Risk Model, a model for step-stress experiments that generalizes the Cumulative Exposure Model discussed by Nelson. Assuming different parametric forms for the hazard function, we derive the MLEs and Least Squares Estimators of the model parameters. We also discuss optimal estimation of the change-points.