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 doing so, we demonstrate the importance of modelling the interactions between the system components by showing their effect on component lifetime reduction.
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