For highly reliable products, accelerated thermal degradation tests are efficient to provide feedback on reliability information. In accelerated thermal degradation tests, the degradation data collected at the elevated temperatures are used to extrapolate the performance of products at the normal temperature. An important tool in such extrapolation is the Arrhenius model, in which the activation energy is generally assumed to be constant. However, in some practical accelerated thermal degradation tests of polymeric materials, a variation of the underlying degradation mechanism is induced when the temperature rises to a certain high level, resulting in a change in the activation energy. Motivated by this phenomenon, we propose a two-stage Arrhenius model. The two stages correspond to the lower and higher temperature ranges with different activation energies. Then, this new model is incorporated to the degradation model, yielding a novel hierarchical model for the accelerated thermal degradation test data from polymeric materials involving a mechanism variation. Furthermore, the Bayesian method is adopted for parameter inference, and the lifetime distribution is obtained subsequently. A practical example of polysiloxane rubbers demonstrates the effectiveness of the proposed model.

对于高度可靠的产品，加速的热降解测试可以有效地提供有关可靠性信息的反馈。在加速热降解测试中，在高温下收集的降解数据用于推断产品在常温下的性能。这种外推的一个重要工具是Arrhenius模型，该模型中的活化能通常被认为是恒定的。然而，在聚合物材料的一些实际的加速热降解测试中，当温度升高到一定高水平时，引起潜在的降解机理的变化，导致活化能的变化。受此现象的启发，我们提出了一个两阶段的Arrhenius模型。这两个阶段分别对应具有不同活化能的较低和较高的温度范围。然后，将此新模型合并到降解模型中，从而为涉及机制变化的聚合材料的加速热降解测试数据提供了一个新颖的分层模型。此外，采用贝叶斯方法进行参数推断，然后获得寿命分布。聚硅氧烷橡胶的实际例子证明了所提出模型的有效性。然后获得寿命分布。聚硅氧烷橡胶的实际例子证明了所提出模型的有效性。然后获得寿命分布。聚硅氧烷橡胶的实际例子证明了所提出模型的有效性。