Abstract: A method for alarm monitoring abnormal conditions associated with a process operation includes collecting N sample data representing one or more parameters of a process, determining a distribution type of the sample data, obtaining an alarm monitoring strategy associated with the distribution type, and monitoring the process using the alarm monitoring strategy. The distribution type may be single-constant, multi-level discrete, normally distributed, continuous non-normally distributed, cyclical trend-up/down, and drifting away after a period maintenance. The alarm monitoring strategy includes a unilateral or bilateral control chart. The one-side control chart has either an upper control limit (UCL) of (100?p) or a lower control limit (LCL) of (p), and the two-sided control chart has a UCL of (100?p/2) and an LCL of (p/2), where p is a predetermined false alarm rate which determines the number N. The control limit may be a difference between two adjacent sample values of the sample data.

Abstract: A method for alarm monitoring abnormal conditions associated with a process operation includes collecting N sample data representing one or more parameters of a process, determining a distribution type of the sample data, obtaining an alarm monitoring strategy associated with the distribution type, and monitoring the process using the alarm monitoring strategy. The distribution type may be single-constant, multi-level discrete, normally distributed, continuous non-normally distributed, cyclical trend-up/down, and drifting away after a period maintenance. The alarm monitoring strategy includes a unilateral or bilateral control chart. The one-side control chart has either an upper control limit (UCL) of (100?p) or a lower control limit (LCL) of (p), and the two-sided control chart has a UCL of (100?p/2) and an LCL of (p/2), where p is a predetermined false alarm rate which determines the number N. The control limit may be a difference between two adjacent sample values of the sample data.