Reliability assessment of semiconductor devices increasingly requires the consideration of multiple degradation mechanisms acting simultaneously over long stress durations. Conventional lifetime qualification and prediction approaches rely on simplified assumptions that can obscure the interpretation of measured degradation data and lead to large uncertainty when extrapolated over many orders of magnitude in time. A consistent analytical framework is therefore required to relate measured degradation behavior to meaningful reliability metrics. This work presents a general framework for semiconductor device reliability that is consistent with established reliability theory and explicitly accommodates multiple competing degradation mechanisms, consistent with modern JEDEC reliability standards. The framework presented here separates physical degradation processes from analytical representations used to interpret experimental data, allowing the effect of independent mechanisms to be combined without imposing an implied physical model. Degradation behaviors exhibiting sublinear time dependence, which are commonly observed across device technologies, are discussed within this context. We show that common data interpretation practices can introduce systematic errors when ssublinearkinetics are present, particularly regarding lifetime extrapolation. A reformulated analytical representation is introduced that improves clarity and robustness in lifetime extraction while remaining fully compatible with standard reliability theory. This framework supports more consistent reliability assessment and more credible lifetime prediction across materials, devices, and operating conditions.

Bias temperature instability (BTI) degradation is commonly described using empirical power-law kinetics; however, extraction of the time exponent and projection of lifetime remain highly sensitive to baseline definition and data representation. In conventional approaches, the threshold voltage shift is referenced to an initial value that cannot be measured simultaneously with stress, introducing uncertainty that can produce apparent curvature and variability in the extracted exponent. In this work, a baseline-independent linearization method is applied to representative published datasets spanning advanced silicon, SiC MOSFETs, and GaN power devices. By analyzing the measured degradation trajectories directly in a transformed time coordinate, the method removes curvature associated with baseline ambiguity and enables consistent extraction of the effective power-law exponent. Across all material systems examined, the extracted exponent exhibits systematic dependence on applied stress once baseline effects are reduced. This behavior challenges the commonly assumed constant-exponent formulation used in conventional lifetime projections and shows that even modest variations in the exponent can produce large differences in projected time-to-failure. A transformed lifetime representation based on ${\mathrm{T}\mathrm{T}\mathrm{F}}^n$ is introduced, in which the influence of exponent variation is separated from the intrinsic voltage and temperature acceleration of the degradation rate. In this representation, the extracted acceleration parameters become more stable and physically interpretable. This formulation is consistent with standard reliability frameworks, including JEDEC JEP122G, in which the time exponent enters directly into the lifetime expression. These results demonstrate that baseline-independent analysis provides a unified framework for interpreting BTI degradation across disparate semiconductor technologies and suggest that explicit treatment of stress-dependent exponents is required for physically consistent lifetime modeling.