Application of data mining in refinery CIMS

Data mining is the process of discovering interesting knowledge, such as patterns, associations, changes, anomalies and significant structures from large amounts of data stored in databases, data warehouses, or other information repositories. It helps enterprises and companies to make better decision to stay competition in the marketplace. As we know, database system is a subsystem of CIMS. In recent years, CIMS has developed very fast. The database subsystem of CIMS becomes more and more complex. So it is necessary to introduce data mining techniques in CIMS. This paper investigates how to apply data mining techniques to extract useful knowledge from databases and data warehouses of CIMS (contemporary integrated manufacturing system). CIMS here is specially CIMS of process industry, refinery CIMS, for example. While differing approaches abound in the realm of data mining, the use of some types of data mining is necessary to accomplish the goals of today´s CIMS.