Alberto Villalonga
Orcid: 0000-0002-9268-0175
According to our database1,
Alberto Villalonga
authored at least 14 papers
between 2017 and 2023.
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Bibliography
2023
Data-Driven Insights on Time-to-Failure of Electromechanical Manufacturing Devices: A Procedure and Case Study.
IEEE Trans. Ind. Informatics, May, 2023
2022
A two-step machine learning approach for dynamic model selection: A case study on a micro milling process.
Comput. Ind., 2022
2021
Ensemble of convolutional neural networks based on an evolutionary algorithm applied to an industrial welding process.
Comput. Ind., 2021
A decision-making framework for dynamic scheduling of cyber-physical production systems based on digital twins.
Annu. Rev. Control., 2021
2020
Cloud-Based Industrial Cyber-Physical System for Data-Driven Reasoning: A Review and Use Case on an Industry 4.0 Pilot Line.
IEEE Trans. Ind. Informatics, 2020
Training an Under-actuated Gripper for Grasping Shallow Objects Using Reinforcement Learning.
Proceedings of the IEEE Conference on Industrial Cyberphysical Systems, 2020
2019
Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study.
Remote. Sens., 2019
Digital Twin-Based Optimization for Ultraprecision Motion Systems With Backlash and Friction.
IEEE Access, 2019
Optimal Tuning of Cascade Controllers for Feed Drive Systems using Particle Swarm Optimization.
Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019
Proceedings of the 23rd International Conference on System Theory, Control and Computing, 2019
2018
Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.
Sensors, 2018
Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments.
Proceedings of the 16th IEEE International Conference on Industrial Informatics, 2018
Industrial cyber-physical system for condition-based monitoring in manufacturing processes.
Proceedings of the IEEE Industrial Cyber-Physical Systems, 2018
2017
Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization.
Complex., 2017