The degradation process of complex multi-component systems is highly stochastic in nature. A major side effect of this
complexity is that components of such systems may have unexpected reduced life and faults and failures that decrease
the reliability of multi-component systems in industrial environments. In this work we provide maintenance practitioners
with an explanation of the nature of some of these unpredictable events, namely the degradation interactions that
take place between components. We begin by presenting a general wear model where the degradation process of
a component may be dependent on the operating conditions, the component’s own state, and the state of the other
components. We then present our methodology for extracting accurate health indicators from multi-component systems
by means of a time-frequency domain analysis. Finally we present a multi-component system degradation analysis of
experimental data generated by a gearbox accelerated life testing platform. In so doing, we demonstrate the importance
of modelling the interactions between the system components by showing their effect on component lifetime reduction