Author:
Susto Gian Antonio,Terzi Matteo,Beghi Alessandro
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering
Reference14 articles.
1. B. Haddad, S. Yang, L. Karam, J. Ye, N. Patel, M. Braun, Multifeature, Sparse-Based Approach for Defects Detection and Classification in Semiconductor Units, vol (xx), available online http://ieeexplore.ieee.org/document/7557053/.
2. H. Wang, F. Tan, B. Sheng, J. Bian, T. Pan. Run-to-run Control for Semiconductor Manufacturing Processes using Extended State Observer. In IEEE Chinese Control and Decision Conference (2016), pp. 854-857.
3. Y. Zheng, D. Ling, Y.-W. Wang, S.-S. Jang, B. Tao, Model Quality Evaluation in Semiconductor Manufacturing Process with EWMA Run-to-Run Control, (2017), vol. 30(1), pp. 8-16.
4. G.A. Susto, A. Beghi, Dealing with Time-series Data in Predictive Maintenance Problems, IEEE Emerging Technologies and Factory Automation Conference (2016).
5. A. Beghi, L. Cecchinato, C. Corazzol, M. Rampazzo, F. Simmini, G.A. Susto, A One-Class SVM Based Tool for Machine Learning Novelty Detection in HVAC Chiller Systems, 19th World Congress of the International Federation of Automatic Control (2014), pp. 1953-1958.
Cited by
57 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献