  We apply tipping point analysis to measurements of electronic components
commonly used in applications in the automotive or aviation industries and
demonstrate early warning signals based on scaling properties of resistance
time series. The analysis utilises the statistical physics framework with
stochastic modelling by representing the measured time series as a composition
of deterministic and stochastic components estimated from measurements. The
early warning signals are observed much earlier than those estimated from
conventional techniques, such as threshold-based failure detection, or bulk
estimates used in Weibull failure analysis. The introduced techniques may be
useful for predictive maintenance of power electronics, with industrial
applications. We suggest that this approach can be applied to various
electromagnetic measurements in power systems and energy applications.
