For over 25 years, thermal infrared data supplied by satellite-based sensors are used to detect and characterize volcanic ash clouds using a commonly accepted method: the 2-Band reverse absorption technique. This method is based on a two-channel difference model using the opposite extinction features of water-ice and ash particles at 11 and 12 μm wavelengths. Although quite efficient with the supervision of a user, this method shows however some limitations for reliable automated detection of volcanic ash in a real-time fashion. Here we explore a method dedicated to the operational monitoring of volcanic ash that combines the 11–12 μm brightness temperature difference (BTD11–12) with a second brightness temperature difference between channels 8.7 μm and 11 μm, (BTD8.7–11). We first achieve a detailed microphysics analysis of different atmospheric aerosols (volcanic ash, water/ice, sulfuric acid, mineral dust) using optical properties (e.g., extinction efficiency, single scattering albedo and asymmetry parameter) calculated by Mie theory, and showing that BTD8.7–11 can be particularly efficient to remove most of artifacts. Then, we tested this method for eight different eruptions between 2005 and 2011 from six different volcanoes (Mount Etna, Piton de la Fournaise, Karthala, Soufriere Hills, Eyjafjallajökull, and Grimsvötn) using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG) geostationary satellite. We show that between 95.6% and 99.9% of ash-contaminated pixels erroneously identified by the BTD11–12 method (i.e., artifacts) were detected and removed by the 3-Band method. For all eruptions, the 3-Band method shows a high and constant reliability having a false alarm rate in the range 0.002–0.08%, hence allowing operational implementation for automated detection in case of a volcanic crisis.