Design an intelligent CIM system based on data mining technology for new manufacturing processes

Abstract

The purpose of this paper is to explain a specific intelligent CIM (computer integrated manufacturing) system by integrating the following five major subject areas: computer integrated manufacturing, data warehouse, online analytical processing (OLAP), data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of DRAM (dynamic random access memory) prices. The results of this paper are the product yield, the manufacturing cycle time and the frequency of holding lot, which have been improved. The contribution can increase business competitiveness, reduce production cost, and promote the rate of available promise for order.