Processing time prediction method based on SVR in semiconductor manufacturing

作者：Zhu Xue Chu^*; Qiao Fei

来源：Journal of Dong Hua University (english Edition), 2014, 31(2): 98-101.

• Dynamic parameters
• Manual intervention
• Manufacturing Execution System
• Manufacturing informations
• Processing time
• Semiconductor manufacturing
• Support vector regression (SVR)
• Technical standards

The prediction problem of the actual value of the dynamic parameters in the simulation model in semiconductor manufacturing was discussed. Considering the fact that the default value of processing time of one certain equipment in the simulation model was not the same as its actual value, a general data driven prediction model of the processing time was built based on support vector regression (SVR), with the utilization of manufacturing information in manufacturing execution system (MES). The processing time of one certain equipment was highly related to the status of the equipment itself and the wafers being processed. To uncover the relationship of the processing time with the information of historical products, process flow, technical standard of silicon wafers and manual intervention, data were extracted from MES and used to build a prediction model. This model was employed on an ion implantation equipment as a case, and the effectiveness of the proposed method was shown by comparing with other approaches.

• 出版日期2014
• 单位同济大学