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Machine Learning and Artificial Intelligence for Quality 4.0
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Digital Tech Talks
AGENDA
Session 1: Introduction – Remaining Useful Life Calculation
09:00 | Introduction to the Workshop – ML for Quality 4.0 Dr. John Soldatos – INTRASOFT International, Luxembourg |
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09:10 | H2020 QU4LITY: The Vision of Autonomous Quality Angelo Marguglio – H2020 QU4LITY TM, Engineering Ingegneria Informatica S.p.A., Italy Dr. Oscar Lazaro – Innovalia Association, Spain |
09:30 | Deep Neural Networks for RUL Estimation Dr. Thanasis Naskos – ATLANTIS Engineering S.A, Greece |
09:50 | QARMA 4 Industry: A Quantitative Rules Mining Framework for RUL Calculation Dr. Ioannis Christou – INTRASOFT International, Luxembourg |
10:10 | SHORT COFFEE BREAK |
Session 2: Faults, Anomalies and Defects Identification
10:15 | Anomaly Detection Using Unsupervised Learning Techniques Dr. L. (Leo) Kampmeijer – TNO, The Netherlands Rob Snel – TNO, The Netherlands |
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10:35 | Intelligent Data Platforms for Advanced Analytics in Industry by Mondragon Coorporation, Ikerlan and MGEP : A Fagor Arrasate Case study Ekhi Zugasti – MGEP, Spain Xabier de Carlos – IKERLAN, Spain |
11:05 | Failure Identification in Failure Identification in ATLANTIS Smart Maintenance Platform Maria Psarodimou – ATLANTIS Engineering S.A, Greece |
11:25 | SHORT COFFEE BREAK |
Session 3: Product Control and Testing – Concluding Remarks
11:30 | ML based Product Testing and Quality Control Dr. Lukas Schulte – Technical University of Dortmund, Germany |
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11:50 | Improving the build quality in laser powder bed fusion using high dynamic range imaging and model-based reinforcement learning Christian Knaak – Fraunhofer ILT, Germany |
12:10 | Open Discussion – Stakeholders’ Feedback – Engaging with QU4LITY and DFA |
12:55 | Conclusions – Closing Remarks – Workshop Closing |