About
An abnormal situation is a disturbance or series of disturbances in a process that causes plant operations to deviate from their normal operating state. The disturbances may be minimal or catastrophic, and cause production losses or, in serious cases, endanger human life. A disturbance of an industrial process system that an automated control system cannot cope with requires human intervention.
The purpose of this research is to establish and maintain safety of processes through automation and analysis methodologies. Because modern chemical plants are large and complex, early and accurate fault detection and diagnosis is imperative. Effective application of these methods can reduce product rejection rates, limit downtime, and help to attain stringent safety requirements. The central goal of abnormal situation management is to document all possible normal modes of a plant operation and detect deviations from normal behavior. Fault detection and diagnosis have gained a central importance in the chemical process industries over the past decade. This presents a need for fault diagnosis systems which use limited information of the process dynamics and accurately detect, isolate, and identify faults.
What is Abnormal Situation Management and Why is it Important?
An abnormal situation is a disturbance or series of disturbances in a process that causes plant operations to deviate from their normal operating state. The disturbances may be minimal or catastrophic, and cause production losses or, in serious cases, endanger human life. A disturbance of an industrial process system that an automated control system cannot cope with requires human intervention.
Fault Detection and Diagnosis
Fault diagnosis is destined to hold central importance in maintaining a chemical industry after installation of Advanced Process Control system (APCS). MKOPSC has conducted research with a purpose to establish and maintain safety of processes through automation and analysis methodologies. Because modern chemical plants are large and complex, early and accurate fault detection and diagnosis is imperative. Fault detection and diagnosis have gained a central importance in the chemical process industries over the past decade. This presents a need for fault diagnosis systems which use limited information of the process dynamics and accurately detect, isolate, and identify faults.
Optimal Alarm Identification and Management
Another aspect of dealing with abnormal situation is alarm management. It is essential to maximize the time available for operators to respond to faults while keeping the number of alarms triggered at a minimum. Research at MKOPSC focuses in developing a quantitative approach for optimal alarm identification.
All of the above accelerates by the abundance of data becoming available as a result of digitalization of the industry and the variety of analytic techniques (see Also Big data and Machine Learning).
