A5028580322- Advanced Surface Polishing Techniques
- Image Processing Techniques and Applications
- Integrated Circuits and Semiconductor Failure Analysis
- Manufacturing Process and Optimization
- Scheduling and Optimization Algorithms
- Industrial Vision Systems and Defect Detection
- Advanced machining processes and optimization
- Advanced Manufacturing and Logistics Optimization
- Advanced Measurement and Metrology Techniques
Tsinghua University
2021-2022
Defective wafer pattern recognition is important for quality control and yield enhancement in semiconductor fabrication systems. The collected maps are usually imbalanced, which may degrade the performance of classifier. In this paper, a focal auxiliary classifier generative adversarial network (FAC-GAN) defective with imbalanced data proposed. FAC-GAN composed AC-GAN modified loss generation deep neural network. proposed measured on real-world map dataset "WM-811k" it outperforms SVM CNN.
Beyond the widely-studied scheduling of wafers within cluster tools, a novel and important perspective is raised in this paper to tackle an upper-level optimization problem real-world production, i.e., assignment hybrid types wafer lots set tools with parallel modules minimize maximum completion time for lots. The main difficulty addressing such that objective, time, cannot be calculated explicitly beforehand. To make tractable, associated maximal overlap among utilized heuristically...
Chemical mechanical planarization (CMP) is an important manufacturing procedure in semiconductor production. The average material remove rate (MRR) a key indicator which could help engineers assess the process status. Thus, virtual metrology for MRR according to machining becomes meaningful task. In this paper, data-driven method based on Wide & Deep neural network proposed predict MRR. We first extract candidate features from time-series variables statistics and nearest neighbor...