ABSTRACT
This article performs a combined analysis of lab and field data. The lab data are obtained by testing the specimens at high but fixed temperatures. The specimens in the field are subjected to a varying temperature profile. We use an accelerated aging model for the lab data and a cumulative damage version of this model for the field data. A Bayesian analysis provides the necessary quantities to compute prediction intervals for specimens in the field for many years into the future.