| 摘要 |
In a process control data base, intermediate characteristics, processing condition for controlling a characteristic and a final characteristic in a process of manufacturing products are stored as a set of data for each product lot. In Process 1, a set of data for each product lot are prepared. Next, in Process 2, cluster processing is conducted on each set of data obtained in Process 1. In Process 3, using the set of data obtained in Process 2, the intermediate characteristics and the processing condition for controlling a characteristic are inputted and the final characteristic is outputted, and a causal relation between the input and output is quantified by a neural network so as to make a learning model. In a model applying stage, the most appropriate processing condition for controlling a characteristic is retrieved by using the learning model and the intermediate characteristics in the previous steps. |
