Combining SOM and fuzzy rule base for flow time prediction in semiconductor manufacturing factory

Authors:
P. C. Chang;T. W. Liao
Affiliations:
Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, Taoyuan, 32026, Taiwan, ROC;Department of Industrial and Manufacturing Systems Engineering, Louisiana State University, Baton Rouge, LA 70803, USA
Venue:
Applied Soft Computing
Year:
2006

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Abstract

This paper presents a novel approach by combining SOM and fuzzy rule base for flow time prediction in semiconductor manufacturing factory. Flow time of a new order is highly related to the shop floor status; however, the semiconductor manufacturing processes are highly complicated and involve more than hundred of production steps. There is no governing function identified so far among the flow time of a new order and these shop flow status. Therefore, a simulation model which mimics the production process of a real wafer fab located in Hsin-Chu Science-based Park of Taiwan is built and flow time and related shop floor status are collected and fed into the SOM for classification. Then, corresponding fuzzy rule base is selected and applied for flow time prediction. Genetic process is further applied to fine-tune the composition of the rule base. Finally, using the simulated data, the effectiveness of the proposed method is shown by comparing with other approaches.