AlarmSoft: An Advanced Cloud-based Alarm Management Application

Modern data acquisition systems allow collection and storage of huge data from process plants. The data set includes sensor readings for the process variables, alarms and events (A&E) log which contains historical alarm data for the plant as well as non-numerical linguistic records of operator interventions and actions. Process data, A&E log, operational records and piping and instrumentation diagram (P&ID) contain wealth of information about the process. Often this information remain under-utilized due to the unavailability of appropriate data mining tools. This paper proposes a comprehensive cloud-based framework that facilitates data collection from various sources into an integrated database, process and analyze data, and display the results in precise visual forms. The application has the capability to analyze huge sets of data in a computationally efficient way. There are four main functions, which are “Data Selection” to select desired processing unit, variables, time range, and parameters tuning; “Visualization” displays the results of the analysis done on process measurements and A&E log data for specified time period; “Alarm Design” allows the user to re-design an alarm configuration for a specific process variable; “Causality Analysis” discovers the relationships between process variables and shows the root cause of an event involving multiple alarms. An industrial case study has been utilized to illustrate the effectiveness and practicability of the platform.