Prediction Modeling for Ingot Manufacturing Process Utilizing Data Mining Roadmap Including Dynamic Polynomial Neural Network and Bootstrap Method

摘要

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation, and then modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters.