APPLYING RULE BASE EXPERT SYSTEM FOR ALARM MANAGEMENT IN OIL REFINERY

Expert system has been used since mid 1960’s to assist human in making decisions. This is especially true when the decision maker is not an expert and need to make a resolution in timely manner. To help lessen the burden of human and also to lessen the probability of error, an expert knowledge is captured and put into a knowledge base for future reference. In an oil refinery, alarm management is crucial in everyday processing management. One of the functions of alarm management is to handle and react to alarm triggering that is caused either by abnormalities in process flow or other natural causes such as lightning and rain. Thus this paper presents Alarm Management Advisory System (AMAS), a system for advising and guiding in managing alarm in oil refinery. It captures the expertise’s knowledge and then store and represents it using rule-based. This prototype system will be like an advisor to help in giving out solutions to handle situations based on the knowledge captures from the expertise and only need to be executed by the engineers without further advice or faraway calls to the experts. This will make the operation less dependent on human factors.