This paper proposes a Bayesian framework for applying a gamma process model for reliability analysis in structural engineering under time–varying stochastic loads. We focus on an important application to engineered wood products and thereby demonstrate how the proposed methodology can be implemented in practice. We use a gamma process to characterize the degradation over time in each piece of lumber, allowing for variability between pieces when external forces from loads are applied to a population of lumber. We propose a model for the shape parameter to accommodate time–varying loads. Our approach is compared with traditional accumulated damage models. Our statistical analysis of experimental data highlight the limitations of using accelerated testing to assess long–term reliability, as seen in the wide posterior intervals. This suggests the need for more comprehensive testing in future applications, or to encode appropriate expert knowledge in the priors used for Bayesian analysis.