Intelligent systems for risk management in industrial processes

Nowadays, the supervision process of industrial installations is more and more complex involving the automation of their control. A malfunction generates an avalanche of alarms. The operator in charge of the supervision must face the incident and executes right actions to recover a normal situation. Generally he is drowned under a great number of alarms. To eliminate the risk of incident, expert systems are designed to help the operator finding the main alarm responsible of the malfunction. This paper shows the limitations of human management of risky situations and the need of knowledge-based systems to assist them monitoring the industrial process and diagnosing abnormal situations.