Alarm Data Analysis for Safe Plant Operations: Case Study of Ethylene Plant

Abstract Sequential alarms are sets of alarms occurring in succession within a short period of time after triggering an initial warning alarm about an abnormality. These types of alarms reduce the ability of plant operators to cope with operation abnormalities because critical alarms are often lost in numerous other correlated ones. Previously, we proposed an identification method for sequential alarms buried in noisy plant operation data using dot matrix. The dot matrix method is a sequence alignment method for identifying similar regions in DNA or RNA, which may be a consequence of functional, structural, or evolutionary relationships between sequences. In this case study, we use this dot matrix method with operation data from an industrial ethylene plant. The results revealed that sequential alarms in a high volume of operation data from the industrial ethylene plant could effectively be identified using the dot matrix method.