Alarm overload in modern chemical plants presents many difficulties in decision and diagnosis. Management and optimization of alarm information are challenging work that must be confronted everyday. A new system alarm optimization technique, based on a fuzzy clustering ranking (FCR) algorithm, is proposed according to the correlativity among process-measured variables. The fuzzy clustering method is used to rationally group and cluster the information matrix of alarm variables to effectively decrease alarms under safety production. Moreover, the fuzzy difference driving (FDD) algorithm is used to rank the clustering center and alarm variables in every cluster, based on objective process characteristics. Furthermore, the validity of the proposed algorithm and solution is verified by application of a practical ethylene cracking furnace alarm system. The proposed method is an effective and reliable alarm-management method that can optimize process operation and improve plant safety in the chemical industry. (C) 2005 American Institute of Chemical Engineers.