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Reporitory of past Ph.D. dissertations

Publications Lists     [ all BibTeX ]  

Publications of keyword: Industry 4.0
20XX
A. Cenedese, F. Tramarin, S. Vitturi, A. Et. Comparative assessment of different OPC UA open–source stacks for embedded systems. IEEE Conference on Emerging Technologies and Factory Automation (ETFA2019) [accepted], 20XX   [BibTeX]  
G.A. Susto, M. Maggipinto, F. Zocco, S. McLoone. Induced Start Dynamic Sampling for Wafer Metrology Optimization. IEEE Transactions on Automation Science and Engineering, vol. (to appear), 20XX   [BibTeX]  
A. Morato, S. Vitturi, A. Cenedese, G. Fadel, F. Tramarin. The Fail Safe over EtherCAT (FSoE) protocol implemented on the IEEE 802.11 WLAN. IEEE Conference on Emerging Technologies and Factory Automation (ETFA2019) [accepted], 20XX    [ abstract ] [BibTeX]  
R. Fantinel, A. Cenedese. Vision-based inspection system for metallic surfaces: CNN driven by features. Quality Control by Artificial Vision Conference (QCAV 2019) - [accepted] - Awarded for the "Most Innovative Application", 20XX    [ abstract ] [BibTeX]  
2019
M. Carletti, C. Masiero, A. Beghi, G.A. Susto. A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study. Procedia Manufacturing, 2019   [BibTeX]  
M. Maggipinto, A. Beghi, G.A. Susto. A Deep Learning-based Approach to Anomaly Detection with 2-Dimensional Data in Manufacturing. International Conference on Industrial Informatics (INDIN), pp. 187 -- 191, 2019    [ abstract ] [BibTeX]  
L. Brunelli, C. Masiero, D. Tosato, A. Beghi, G.A. Susto. Deep Learning-based Production Forecasting in Manufacturing: a Packaging Equipment Case Study. Procedia Manufacturing, 2019   [BibTeX]  
M. Carletti, C. Masiero, A. Beghi, G.A. Susto. Explainable Machine Learning in Industry 4.0: Evaluating Feature Importance in Anomaly Detection to Enable Root Cause Analysis. 2019 IEEE International Conference on Systems, Man, and Cybernetics, 2019    [ abstract ] [url] [BibTeX]  
N. Trivellin, D. Barbisan, M. Pietrobon, D. Badocco, P. Pastore, A. Cenedese, G. Meneghesso, E. Zanoni, M. Meneghini. Near-UV LED-based systems for low-cost and compact oxygen-sensing systems in gas and liquids. SPIE Conference - Photonics West Opto Proc. SPIE 10940, Light-Emitting Devices, Materials, and Applications, pp. 109400V, 2019    [ abstract ] [url] [BibTeX]  
M. Maggipinto, G.A. Susto, F. Zocco, S. McLoone. What are the Most Informative Data for Virtual Metrology? A use case on Multi-Stage Processes Fault Prediction. IEEE Conference on Automation Science and Engineering, 2019   [BibTeX]  
2018
M. Maggipinto, M. Terzi, C. Masiero, A. Beghi, G.A. Susto. A Computer Vision-inspired Deep Learning Architecture for Virtual Metrology modeling with 2-Dimensional Data. IEEE Transactions on Semiconductor Manufacturing, vol. 31(3), pp. 376 - 384, 2018    [ abstract ] [url] [BibTeX]  
M. Maggipinto, C. Masiero, A. Beghi, G.A. Susto. A Convolutional Autoencoder Approach for Feature Extraction in Virtual Metrology. Procedia Manufacturing, 28th International Conference on Flexible Automation and Intelligent Manufacturing, vol. 17, pp. 126-133, 2018    [ abstract ] [url] [BibTeX]  
G.A. Susto, M. Maggipinto, F. Zocco, S. McLoone. A Dynamic Sampling Approach for Cost Reduction in Semiconductor Manufacturing. Procedia Manufacturing, 28th International Conference on Flexible Automation and Intelligent Manufacturing, vol. 17, pp. 1031-1038, 2018    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Schirru, S. Pampuri, A. Beghi, G. De nicolao. A Hidden-Gamma Model-Based Filtering and Prediction Approach for Monotonic Health Factors in Manufacturing. Control Engineering Practice, vol. 74, pp. 84-94, 2018    [ abstract ] [url] [pdf] [BibTeX]  
S. McLoone, A.B. Johnston, G.A. Susto. A Methodology for Efficient Dynamic Spatial Sampling and Reconstruction of Wafer Profiles. IEEE Transactions on Automation Science and Engineering, vol. 15(4), pp. 1692-1703, 2018    [ abstract ] [url] [pdf] [BibTeX]  
S. Vitturi, A. Morato, A. Cenedese, G. Fadel, F. Tramarin, R. Fantinel. An Innovative Algorithmic Safety Strategy for Networked Electrical Drive Systems. 16th International Conference on Industrial Informatics (INDIN18), pp. 368--373, 2018    [ abstract ] [url] [BibTeX]  
S. McLoone, F. Zocco, M. Maggipinto, G.A. Susto. On Optimising Spatial Sampling Plans for Wafer Profile Reconstruction. 3rd IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control, 2018    [ abstract ] [url] [BibTeX]  
2017
G.A. Susto. A Dynamic Sampling Strategy based on Confidence Level of Virtual Metrology Predictions. IEEE/SEMI Advanced Semiconductor Manufacturing Conference, pp. 78-83, 2017    [ abstract ] [url] [BibTeX]  
G.A. Susto, M. Terzi, A. Beghi. Anomaly Detection Approaches for Semiconductor Manufacturing. Procedia Manufacturing, 27th International Conference on Flexible Automation and Intelligent Manufacturing, vol. 11, pp. 2018-2024, 2017    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi, S. McLoone. Anomaly Detection through on-line Isolation Forest: an Application to Plasma Etching. IEEE/SEMI Advanced Semiconductor Manufacturing Conference, 2017    [ abstract ] [url] [BibTeX]  
M. Terzi, C. Masiero, A. Beghi, M. Maggipinto, G.A. Susto. Deep Learning for Virtual Metrology: Modeling with Optical Emission Spectroscopy Data. IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI), 2017    [ abstract ] [url] [BibTeX]  
2016
G.A. Susto, A. Beghi. Dealing with Time-Series Data in Predictive Maintenance Problems. Emerging Technologies and Factory Automation, 2016    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Schirru, S. Pampuri, S. McLoone. Supervised Aggregative Feature Extraction for Big Data Time Series Regression. IEEE Transactions on Industrial Informatics, vol. 12, pp. 1243 - 1252, 2016    [ abstract ] [url] [BibTeX]  
2015
G.A. Susto, A. Schirru, S. Pampuri, S. McLoone, A. Beghi. Machine Learning for Predictive Maintenance: a Multiple Classifiers Approach. IEEE Transactions on Industrial Informatics, vol. 11(3), pp. 812 - 820, 2015    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. Pampuri, A. Schirru, A. Beghi, G. De nicolao. Multi-Step Virtual Metrology for Semiconductor Manufacturing: a Multilevel and Regularization Methods-based Approach. Computers & Operations Research, vol. 53, pp. 328–337, 2015    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. McLoone. Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach. 11th IEEE Conference on Automation Science and Engineering, pp. 1218-1223, 2015    [ abstract ] [url] [BibTeX]  
2014
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, pp. 1953-1958, 2014    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. Pampuri, M. Zanon, A.B. Johnston, P.G. O’Hara, S. McLoone. An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance. Conference on Automation Science and Engineering, pp. 806-811, 2014    [ abstract ] [url] [BibTeX]  
S. Pampuri, G.A. Susto, J. Wan, A.B. Johnston, P.G. O’Hara, S. McLoone. Insight Extraction for Semiconductor Manufacturing Processes. Conference on Automation Science and Engineering, pp. 786 - 791, 2014    [ abstract ] [url] [BibTeX]  
M. Zanon, G.A. Susto, S. McLoone. Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach. 19th World Congress of the International Federation of Automatic Control, pp. 1947-1952, 2014    [ abstract ] [url] [BibTeX]  
2013
G.A. Susto, A. Schirru, S. Pampuri, D. Pagano, S. McLoone, A. Beghi. A Predictive Maintenance System for Integral Type Faults based on Support Vector Machines: an Application to Ion Implantation. Automation Science and Engineering (CASE), 2013 IEEE International Conference on, 2013    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi. A virtual metrology system based on least angle regression and statistical clustering. Applied Stochastic Models in Business and Industry, vol. 29(4), pp. 362-376, 2013    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. McLoone, A. Schirru, S. Pampuri, D. Pagano, A. Beghi. Prediction of Integral Type Failures in Semiconductor Manufacturing through Classification Methods. 18-th IEEE Conference on Emerging Technologies and Factory Automation, 2013    [ abstract ] [url] [BibTeX]  
G.A. Susto, A.B. Johnston, P.G. O’Hara, S. McLoone. Virtual Metrology Enabled Early Stage Prediction for Enhanced Control of Multi-stage Fabrication Processes. Automation Science and Engineering (CASE), 2013 IEEE International Conference on, 2013    [ abstract ] [url] [BibTeX]  
2012
G.A. Susto, A. Schirru, S. Pampuri, A. Beghi. A Predictive Maintenance System based on Regularization Methods for Ion-Implantation. 23rd IEEE/SEMI Advanced Semiconductor Manufacturing Conference, pp. 175-180, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi, C. De luca. A Predictive Maintenance System for Epitaxy Processes based on Filtering and Prediction Techniques. IEEE Transactions on Semiconductor Manufacturing, vol. 25, pp. 638 - 649, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi. An Information Theory-based Approach to Data Clustering for Virtual Metrology and Soft Sensors. 3rd International conference on CIRCUITS, SYSTEMS, CONTROL, SIGNALS, pp. 198--203, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Schirru, S. Pampuri, G. De nicolao, A. Beghi. An Information-Theory and Virtual Metrology-based approach to Run-to-Run Semiconductor Manufacturing Control. Automation Science and Engineering (CASE), 2012 IEEE International Conference on, pp. 358 -363, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. Pampuri, A. Schirru, G. De nicolao, S. McLoone, A. Beghi. Automatic Control and Machine Learning for Semiconductor Manufacturing: Review and Challenges. 10th European Workshop on Advanced Control and Diagnosis, 2012    [ abstract ] [BibTeX]  
G.A. Susto, S. Pampuri, A. Schirru, G. De nicolao, S. McLoone, A. Beghi. Automatic Control and Machine Learning for Semiconductor Manufacturing: Review and Challenges. 10th European Workshop on Advanced Control and Diagnosis, 2012    [ abstract ] [url] [BibTeX]  
A. Schirru, G.A. Susto, S. Pampuri, S. McLoone. Learning from Time Series: Supervised Aggregative Feature Extraction. 51st IEEE Conference on Decision and Control, pp. 5254--5259, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi. Least Angle Regression for Semiconductor Manufacturing Modeling. Control Applications (CCA), 2012 IEEE International Conference on, pp. 658--663, 2012    [ abstract ] [url] [BibTeX]  
S. Pampuri, A. Schirru, G.A. Susto, G. De nicolao, A. Beghi, C. De luca. Multistep Virtual Metrology Approaches for Semiconductor Manufacturing Processes. Automation Science and Engineering (CASE), 2012 IEEE International Conference on, pp. 91 -- 96, 2012    [ abstract ] [url] [BibTeX]  
G.A. Susto, S. Pampuri, A. Schirru, A. Beghi. Optimal Tuning of Epitaxy Pyrometers. 23rd IEEE/SEMI Advanced Semiconductor Manufacturing Conference, pp. 294-299, 2012    [ abstract ] [url] [BibTeX]  
2011
G.A. Susto, A. Beghi, C. De luca. A Predictive Maintenance System for Silicon Epitaxial Deposition. Proceeding of 7th IEEE International Conference on Automation Science and Engineering, pp. 262-267, 2011    [ abstract ] [url] [BibTeX]  
G.A. Susto, A. Beghi, C. De luca. A Virtual Metrology System for Predicting CVD Thickness with Equipment Variables and Qualitative Clustering. Proceeding of 16th IEEE International Conference on Emerging Technologies and Factory Automation, pp. 1-4, 2011    [ abstract ] [url] [BibTeX]