Failure prediction & maintenance scheduling for semiconductor wafer fabrication based on adaptive neuro-fuzzy inference system

To solve the failure prediction problem of semiconductor wafer fabrication, Adaptive Neuro-Fuzzy Inference System (ANFIS) was applied to construct a failure prediction model. In this model, subtractive clustering algorithm was used to confirm the original structure of fuzzy inference model, and a hybrid algorithm consisted of the least-squares method and the back propagation gradient descent method was adopted to optimize the parameters. Through verification with the testing data, the model was with good fitting ability and the high recognition accuracy, which helped to forecast important information effectively such as equipment name of the contingent equipment failure. Finally, by embedding the failure prediction into the original maintenance scheduling, a new maintenance scheduling strategy was established. This model was simulated in a semiconductor wafer fabrication, and results revealed satisfactory scheduling performance.