Industrial plants, especially on mining, metal processing, energy and chemical/petrochemical processes require integrated management of all the events that may cause accidents and translate into alarms. Process alarm management can be formulated as an event-based pattern recognition problem in which temporal patterns are used to characterize different typical situations, particularly at startup and shutdown stages. In this paper, a new layer based on a diagnosis process is proposed over the typical layers of protection in industrial processes. Considering the alarms and the actions of the standard operating procedure as discrete events, the diagnosis step relies on situation recognition to provide the operators with relevant information about the failures inducing the alarm flow. The new concept of super alarms is based on a methodology with a diagnosis step that permits generate these types of superior alarms. For example, the Chronicle Based Alarm Management (CBAM) methodology involves different techniques to take the hybrid aspect and the standard operational procedures of the concerned processes into account.