## 2 Related Work  
In engineering, the development of a model has been used traditionally to understand component failure mode progression. The development of PoF or physics-based models (PbMs), that incorporate the ability to assess damage to a component, taking into account operating conditions and giving a cumulative damage assessment, provides a basis to evaluate the distribution of the remaining useful life (RUL). It is deduced from a literature review that the actual availability of physics of failure models is limited. This implies that, at present, few PoF models incorporate the ability to predict damage parameters with an acceptable confidence boundary over steady-state and transient loads, temperatures, and other variables. One such model that has found prevalence in prognostic literature is the Paris law for crack propagation [1; 2]. Here, the crack growth process was simulated to yield normally distributed crack lengths, which were used within a Bayesian framework to update the parameters of the degradation model (e.g., Paris' law). The degradation model was initially fed by the results of a stress analysis from a gear dynamic model or finite element model. The distributions of the uncertainty factors were updated via Bayesian inference using the condition monitoring data (simulated crack lengths), and an estimation of the RUL based on the degradation model was provided. [PERSON] et al. [3] proposed a physics-based (first principle) modelling and prognostics approach for electrolytic capacitors. Electrolytic capacitors and MOSFETs (Metal Oxide Semiconductor Field Effect Transistors) are the two major components that cause degradation and failure in DC-DC converters. The paper studies the effects of accelerated ageing due to thermal stress on sets of capacitors, with the focus on deriving first principle degradation models for thermal stress conditions. The degradation data forms the basis for developing the model-based remaining life prediction algorithm. Finally, the data is used to derive accurate models of capacitor degradation and use them to predict performance changes in DC-DC converters. A PoF-based prognostic method for power electronic modules proposed by [4] allows the reliability performance of power modules to be assessed in real time. A compact thermal model is initially constructed to investigate the relationship between the power dissipation and the temperature in the power module. This relationship can be used for fast calculation of junction temperature and the temperatures at each interface inside power modules. The predicted temperature profile is then analyzed using a rain-flow counting method so that the number of thermal cycles with different temperature ranges can be calculated. A reduced order thermo-mechanical model is also constructed to enable a fast calculation of the accumulated plastic strain in the solder material under different loading conditions. The information of plastic strains is then used in the lifetime prediction model to predict the reliability of the solder interconnect under each regular loading condition. In [5], the researchers suggested a lifetime prediction methodology for assembled PCBs using characteristic failure curves from a fracture mechanics-based model and the local loading simulations. They provided a viable replacement for the board level drop test (BLDT), however, they could not carry out the PCB lifetime prediction using accelerated testing methods and finite element analysis post simulations. [PERSON] et al. [6] processed the solder fatigue coefficients and finite element analysis (FEA) using a MATLAB routine for the lifetime prediction of flip chip (fitted on a PCB) solder joints. They analyzed and compared the significant features of microstructural modification and crack paths under individual temperatures and vibration cycling, in addition to the combined loading experiments with the lifetime model built on the Coffin-Manson-Basquin relationship.