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A Look-Ahead Fuzzy Back Propagation Network for Lot Output Time Series Prediction in a Wafer Fab

机译:晶圆厂批量输出时间序列预测的超前模糊反向传播网络

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Lot output time series is one of the most important time series data in a wafer fab (fabrication plant). Predicting the output time of every lot is therefore a critical task to the wafer fab. To further enhance the effectives and efficiency of wafer lot output time prediction, a look-ahead fuzzy back propagation network (FBPN) is constructed in this study with two advanced features: the future release plan of the fab is considered (look-ahead); expert opinions are incorporated. Production simulation is also applied in this study to generate test examples. According to experimental results, the prediction accuracy of the look-ahead FBPN was significantly better than those of four existing approaches: multiple-factor linear combination (MFLC), BPN, case-based reasoning (CBR), and FBPN without look-ahead, by achieving a 12%~37% (and an average of 19%) reduction in the root-mean-squared-error (RMSE) over the comparison basis - MFLC.
机译:批输出时间序列是晶圆厂(制造工厂)中最重要的时间序列数据之一。因此,预测每批次的输出时间是晶圆厂的关键任务。为了进一步提高晶圆批输出时间预测的有效性和效率,本研究构建了具有两个高级功能的超前模糊反向传播网络(FBPN):考虑了晶圆厂的未来发布计划(超前);纳入专家意见。生产模拟也用于本研究中以生成测试示例。根据实验结果,前瞻性FBPN的预测精度明显优于四种现有方法:多因素线性组合(MFLC),BPN,基于案例的推理(CBR)和不进行前瞻性的FBPN,通过在比较基础上将MFLC的均方根误差(RMSE)降低了12%〜37%(平均为19%)。

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