This study proposes a numerical methodology based on the application of first-, second-, and third-order derivatives to analyse the evolution of the coefficient of friction (CoF) obtained from ball-on-disc (BoD) wear tests. The approach aims to provide an objective and quantitative identification of mechanisms, wear stages, and transition points, overcoming the subjectivity commonly associated with conventional friction curve interpretation. Before derivative computation, the CoF signal was smoothed to reduce experimental noise while preserving the morphological features of the friction curve. The methodology was applied to a newly developed multicomponent Al80Mg10Si5Cu5 high-pressure die casting (HPDC) alloy tested under dry sliding at room temperature (RT). The derivative-based analysis enabled the identification of successive wear stages, from the initial settling and running-in to transient and quasi-stationary regimes, and the determination of characteristic transition points, correlated with wear mechanisms through surface and microstructural analyses. The results demonstrate that the proposed methodology enables an objective determination of the duration and sequence of wear stages, reveals that the transition to stable sliding does not coincide with the maximum CoF value, and improves the identification of highly dynamic early wear regimes that are often underestimated by visual analysis. Due to its low computational cost and reliance on signals commonly available in tribological systems, the proposed derivative-based methodology shows strong potential for real-time friction and wear monitoring, predictive maintenance, and the automation of tribological control systems, although further validation under industrial operating conditions is required.