Novel Outlier-Robust Accelerated Degradation Testing Model and Lifetime Analysis Method Considering Time-Stress-Dependent Factors

Accelerated degradation testing (ADT) data typically exhibit a time-stress-dependent structure, as well as random uncertainties due to time-varying effects and unit-to-unit variations. Existing ADT models based on Brownian motion with drift have successfully represented the fault/failure-based degradation behavior and random uncertainty by assuming that the drift parameter follows a Gaussian distribution. However, these models often lack robustness to outliers, leading to distorted analysis, affecting parameter estimation, model accuracy, decision-making, risk assessment, and potentially overlooking the influence of stress factors. A novel robust ADT model based on the Wiener process and its corresponding lifetime analysis method are proposed to address these issues. The proposed approach improves upon traditional ADT models by making the drift parameter follow a t-distribution rather than a Gaussian distribution, which can reduce sensitivity to outliers in real degradation processes. In addition, the proposed method allows for the simultaneous consideration of time-stress-dependent factors in the ADT model, facilitating the derivation of a closed-form robust ADT formulation. Subsequently, the lifetime is analyzed based on the ADT model using the first hitting time method in a probabilistic framework. The proposed method is applied to stress relaxation data of electrical connectors and compared to three other common methods.