Nowadays, electronic products tend to be economically outdated before their technical end of life has been reached. The ability to analyze and predict the (remaining) technical life of a product would make it possible either to re-use sub-assemblies in the manufacturing process of new products, or to design products for which the technical and economical life match. This requires models to predict and monitor performance degradation profiles. In this paper we report on designed experiments to obtain such models. We show how wavelet analysis can be used to extract features from electrical signals. These features are analyzed using Analysis of Variance in order to establish relations between these features and performance degradation.