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

Accelerated life testing (ALT) is widely used to obtain reliability information about a product within a limited 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 changing the stress levels are investigated. We discuss the optimal designs under three optimality criteria. They are D-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed is correct. Due to the nature of prediction made from ALT experimental data, attained under the stress levels higher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot be tested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robust designs is also explored.

Name thesis:degree_name

M.Sc. Mathematics and Statistics

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Faculty of Mathematics and Science

Department dc:contributor.department

Department of Mathematics

Grantor

Brock University

Year dc:date.issued

2015

Author dc:creator

• Huang, Wan-yi

• Step-stress accelerated life test
• Cox's proportional hazards model
• Robust design
• Maximum likelihood estimation
• Reliability estimation

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/10464/7230

OAI identifier oai:identifier

oai:brocku.scholaris.ca:10464/7230