Collaborator · ESD
Sebastiano Gaiardelli
Postdoctoral Researcher
Chair of Cyber-Physical Systems in Production Engineering, Technical University of Munich
Research interests
Cyber-physical production systems · Production optimisation and reconfiguration · Model-Based Systems Engineering · Digital twins · Service-oriented manufacturing
Sebastiano Gaiardelli is a Postdoctoral Researcher at the Technical University of Munich, where he works at the Chair of Cyber-Physical Systems in Production Engineering. He completed his PhD in Computer Science at the University of Verona with the thesis “Dynamo: A Framework to Verify, Optimize and Reconfigure Flexible Manufacturing Systems”, after MSc and BSc studies in Computer Science and Engineering at Verona.
His research focuses on making cyber-physical production systems adaptable without losing a rigorous model of their constraints and behaviour. He has worked on production scheduling, reconfiguration and optimisation; hierarchical and graph-based models of manufacturing processes; Model-Based Systems Engineering; service-oriented manufacturing architectures; and the integration of engineering models with ontologies. In DeFacto, this work contributed to design-automation techniques for flexible smart factories.
Sebastiano has also worked on industrial monitoring, anomaly detection and digital-twin infrastructure, including the GLACIER and Frost research lines. These activities connect executable models of production equipment with data services and control software so that alternative configurations can be analysed and tested before changes reach the plant. He is also a co-founder and scientific advisor of FACTORYAL S.r.l., a University of Verona spin-off focused on factory-automation software.
Publications
2024
A Data Fusion Service-Oriented Infrastructure for Production Line Monitoring
ICIT
A Multi-Material and Multi-Scenario Dataset for Additive and Subtractive Manufacturing Operations
ETFA
An AI-Enabled Framework for Smart Semiconductor Manufacturing
DATE
Design Automation for Cyber-Physical Production Systems: Lessons Learned from the DeFacto Project
DATE
Enabling Service-Oriented Manufacturing Through Architectures, Models, and Protocols
IEEE Access
Integrating Modeling Languages with Ontologies in the Context of Industry 4.0
ICIT
RRPDG: A Graph Model to Enable AI-Based Production Reconfiguration and Optimization
IEEE Trans. Ind. Informatics
VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge
DAC
2023
2022
A Hierarchical Modeling Approach to Improve Scheduling of Manufacturing Processes
ISIE
A Software Architecture to Control Service-Oriented Manufacturing Systems
DATE
Integrating Smart Contracts in Manufacturing for Automated Assessment of Production Quality
IECON
On the Impact of Transport Times in Flexible Job Shop Scheduling Problems
ETFA
SMART-IC: Smart Monitoring and Production Optimization for Zero-waste Semiconductor Manufacturing
LATS

