Among systems that provide sensor data of their performance, one approach to prognostic estimation is forecasting, i.e. prediction of measurable parameters and comparison of predicted values against established operational limits. Forecasting can be attempted statistically, or can be based on rigorous physical simulation. However, combining these approaches is difficult where system mode behavior or timing of system activities is uncertain, limiting the accuracy or applicability of a forecast.

Understanding aging mechanisms of electronic components is of extreme importance in the aerospace domain where they are part of numerous critical subsystems including avionics. In particular, power MOSFETs are of special interest as they are involved in high voltage switching circuits such as drivers for electrical motors. With increased use of electronics in aircraft control, it becomes more important to understand the degradation of these components in aircraft specific environments.

One of the most important issues when dealing with PHM developments is the availability of adequate sensors to provide measures that indicate the health state of a component or system. Installation of additional sensors for such purpose usually implies increments in costs and weight and reduction of reliability and availability. Sometimes equivalent information can be inferred from other available sources, allowing the design of PHM solutions with no need for additional sensors. The power consumed by a set of components may provide information concerning their health states.