126 – New Development in Reliability Models and Innovative Applications
Parameter Estimation Using EM Algorithm for Constant-Stress and Step-Stress Accelerated Life Tests Under Interval Monitoring
Tianyu Bai
University of Texas at San Antonio
David Han
University of Texas at San Antonio
Accelerated life tests quickly produce information on the lifetime distribution of a test unit by running the tests at higher stress levels than normal operating conditions. Using a regression model, the lifetime parameter at the normal design stress is then estimated via extrapolation. Recently, the design optimization of accelerated life tests has been studied by many authors but the associated inference for the regression parameters has not been. In this work, the EM algorithm is used to determine the maximum likelihood estimates of the regression parameters for time constrained exponential failure data from the constant-stress and step-stress accelerated life tests under interval monitoring. It is demonstrated that the method is feasible as well as easy to implement. The proposed method is illustrated using a real engineering case study.