Artificial Intelligence (AI), Machine Learning (ML), Intelligent Manufacturing and Automation will revolutionize the fields of Nanotechnologies, Organic Electronics, Advanced Materials, Green Energy, Nanomedicine, Bioelectronics, Nano-Manufacturing etc by providing robust and innovative solutions ranging to material discovery and selection, to processes and device optimization and performance, to reliable and cost-effective manufacturing. It has the potential to strongly accelerate material discovery, optimizing device design, enhancing quality control, predicting device performance, improving process efficiency, enabling predictive maintenance, and providing data-driven insights. As AI and ML technologies, and Intelligent Manufacturing continue to develop, their impact on Nanotechnologies, Organic Electronics and Advanced Materials is expected to grow even further, paving the way for innovative and transformative applications in various fields, including Energy, Batteries, Lighting, Displays, Sensors, Energy Efficient Buildings, Energy and Hydrogen Storage, Healthcare, IoT, etc.
The Workshop on AI, ML, Intelligent Manufacturing and Automation combined with nanotechnologies, organic electronics, advanced materials, energy and manufacturing engineering aims to bring industry professionals, experts, learners, and researchers to one platform to discuss Technology, Engineering and Data Analytics in depth, and to explore new paths in the field with incredible subjects and discussions to foster collaborative learning. These discussions will open the door to new ideas, inspire students and help create innovative applications and a healthy community and economy. Participants will gain insights into the latest advancements in AI, ML, Intelligent Manufacturing and Automation techniques applied to these disciplines, including the development of advanced materials, device design, patterning, precision metrologies and quality control, characterization and testing, multiphysics and multiscale modelling and analysis.
Workshop topics include (but not limited to):
- Predictive Maintenance with AI
- Quality Control and Defect Detection with AI
- Supply Chain Optimization using AI
- AI-powered Robotics in Manufacturing
- Smart Manufacturing and IoT Integration
- Human-Robot Collaboration in Manufacturing
- AI-driven Energy Management in Manufacturing
- Cybersecurity for AI-enabled Manufacturing Systems
- AI for Inventory Optimization
- Fault Detection and Diagnosis using Machine Learning
- AI-driven Product Design and Customization
- Real-time Process Monitoring and Control with AI
- Machine Learning for Demand Forecasting
- AI-enabled Predictive Analytics for Manufacturing Operations
- AI, Automations and Industry 4.0 and 5.0 in Nano-Manufacturing
- Natural Language Processing (NLP) for Manufacturing Data Analysis
- AI-driven Digital Twin Technology for Manufacturing
- Explainable AI (XAI) in Manufacturing
- AI Ethics and Governance in Manufacturing
- Machine Learning Approaches for Materials Design
- High-Throughput Screening using AI
- Generative Models for Materials Synthesis
- Quantum Machine Learning for Materials Modeling
- Data-driven Approaches to Materials Informatics
- AI-enabled Property Prediction for Materials
- Materials Genome Initiative and AI
- AI for Sustainable Materials Design
- Challenges and Opportunities in AI-driven Materials Science
Workshop International Organizing Committee
S. Logothetidis, Nanotechnology Lab LTFN, AUTh, Greece
A. Afantitis, NovaMechanics Ltd & Entelos Institute, Cyprus
S. Albarqouni, University of Bonn, Germany
Y. Chrysanthou, Department of Computer Science, University of Cyprus, Cyprus
A. Franco, University Amiens Picardie Jules Verne, France
T. Karakasidis, University of Thessaly, Greece
A. Kneer, TinniT Technologies GmbH, Germany
E. Lidorikis, University of Ioannina, Greece
G. Melagraki, Hellenic Military Academy, Greece
M. Polycarpou, Department of Electrical and Computer Engineering, University of Cyprus, Cyprus
H. Sarimveis, National Technical University of Athens, Greece
D. Tzovaras, Centre of Research & Technology - Hellas, Greece
G. Volonakis, University of Rennes 1, France
Organized by:
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HORIZON EUROPE - COPE-Nano: "Centre Of Excellence For Organic, Printed Electronics & Nanotechnologies" www.cope-nano.eu |
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EU HORIZON EUROPE - Flex2Energy: "Automated Manufacturing Production Line for Integrated Printed Organic Photovoltaics" www.flex2energy.eu |
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H2020 REALNANO: "In-line and Real-time digital nano-characterization technologies for the high yield manufacturing of Flexible Organic Electronics" www.realnano-project.eu |
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EU H2020-MUSICODE: "An experimentally-validated multi-scale materials, process and device modelling & design platform enabling non-expert access to open innovation in the Organic and Large Area Electronics Industry" www.musicode.eu |
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EU H2020 - nanoMECommons: "Harmonisation of EU-wide nanomechanics protocols and relevant data exchange procedures, across representative cases; standardisation, interoperability, data workflow (nanoMECommons)" www.nanomecommons.net |
