Using data mining technology to build an intelligent manufacturing system for semiconductor industry

In this paper, we propose a flexible three-tier architecture for data mining in semiconductor manufacturing. The architecture allows a high-performance implementation of data mining techniques using association rule. The prototype is able to mine patterns from large data sets that reside in databases. There are benefits to use the data mining control system that is implemented by association rule in computer integrated manufacturing (CIM) environment. The result shows that the proposed intelligent manufacturing system can improve product yield rate and reduce cycle time in semiconductor manufacturing. It could find the best machines of process machine sets that affect processes. It also enhances wafer yield accuracy, reduces production costs and promotes the enterprise competitiveness.