The object of alarm rationalization is to check if alarms are set correctly with respect to high and low limits and also to ensure that critical alarms are not missed and that there are as few false alarms as possible. This paper outlines a procedure based on the similarity of correlation maps of physical process variables and their alarm history in combination with process connectivity information through causal maps to suggest optimal alarm settings. The process of correlation analysis clearly takes into account the multivariate nature of the process and thereby reduces the number of false and missed alarms.
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