Batch Processes Monitoring: Identification Stage

MARCO CEDEÑO; LEANDRO RODRIGUEZ; MABEL SÁNCHEZ

Atlanta

Congreso; 2014 AIChE Annual Meeting; 2014

American Institute of Chemical Engineers

In this work the monitoring strategy presented by Cedeño et al. (2012) is extended to tackle batch processes. The technique uses only the Hoteling statistics (T2) for detection purposes. The identification of the faulty set of observations is performed by applying the NICN concept to calculate the variable contributions to the inflated statistic, and then using cluster theory to point out the suspicious measurements. It avoids the setting of empirical parameters. A fed-batch penicillin fermentation benchmark (Birol et al., 2002) is used to analyze the performance of the presented strategy, which is compared with the most commonly used statistical monitoring strategies.