关键词: 半导体生产线, 产出率预测, 非线性规划, 范围预测, BP神经网络

Abstract: To improve the efficiency and accuracy of semiconductor wafer fabrication's throughput rate,an approach which combined mathematical programming and Back Propagation Neural network (BPN) was proposed,which could reduce the complexity of prediction by considering the ignored predicted problem.The throughput rate multiple linear regression model was built by using Principal Component Analysis (PCA) to select key performance indicators,and the linear programming models were used to determine the minimum range of throughput rate.The prediction range parameters were took into nonlinear programming to adjust neural network parameters to get the final forecast result.According to the theoretic analysis and experiments,the proposed method was proved available,the prediction range was more accurate and the forecasting process was relatively simple.

Key words: semiconductor wafer fabrication, throughput rate prediction, nonlinear program, prediction range, back propagation neural network