A SOM-FBPN-ensemble approach with error feedback to adjust classification for wafer-lot completion time prediction

Predicting the completion time of a lot is a critical task to a wafer fabrication plant (wafer fab). Many recent studies have shown that pre-classifying a wafer lot before predicting the completion time was beneficial to prediction accuracy. However, most classification approaches applied in this field could not absolutely classify wafer lots. Besides, whether the pre-classification approach combined with the subsequent prediction approach was suitable for the data was questionable. For tackling these two problems, a self-organization map-fuzzy-back-propagation network-ensemble (SOM-FBPN-ensemble) approach with error feedback to adjust classification is proposed in this study. The proposed methodology has two advanced features: predicting the completion time using a FBPN-ensemble instead of a single FBPN, and feeding back the prediction error to adjust the classification result by the SOM. According to experimental results, the prediction accuracy of the proposed approach was significantly better than those of many existing approaches. Besides, the effects of the two advanced features were also evident.