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Monday 19 September 9:00 - 13:00, 2022
Monday 19 September 9:00 - 13:00, 2022
Co-located with the ECML PKDD 2022
Hybrid: Grenoble (France) & Online
The AI in Manufacturing workshop brings together researchers and practitioners from AI and the area of manufacturing, and especially also people working at the intersection. The workshop provides an opportunity for interaction and networking, and a platform for the dissemination of problem statements, early ideas and work-in-progress presentations for potentially ground-breaking research, in the broad area of AI with application in manufacturing. Our intention is to facilitate AI advances relevant for manufacturing. The scope includes theory, algorithms, systems, and applications related to this topic.
NB. To attend the workshop, it is necessary to register with the ECML-PKDD conference: https://2022.ecmlpkdd.org/index.php/registration/
Detailed schedule
Detailed schedule
9:00 - 9:10 Opening
9:10 - 9:35 Two papers (10+2 minutes each)
Sunanda Gamage, Benjamin Klöpper and Jagath Samarabandu. Experiences with Contrastive Predictive Coding in Industrial Time-Series Classification
Zhong Li and Matthijs van Leeuwen. Feature Selection for Fault Detection and Prediction based on Log Analysis
9:35 - 10:30 Panel ‘Challenges and the Future of AI in Manufacturing’
Moderator:
- Dimitra Gkorou (ASML, The Netherlands)
Panelists:
- William Susanto, Manager of Smart Manufacturing & AI, Supplier Engagement (Micron, Singapore)
- Bappaditya Dey, ML Researcher and Advanced Process Optimization in Semi-conductors (Imec, Belgium)
- Mathias Verbeke, Professor of AI for Industry (KU Leuven, Belgium)
- Duncan Hai Liang Lee, Principal Engineer (Intel, Malaysia)
10:30 - 11:00 Break
10:30 - 11:00 Break
11:00 - 11:50 Keynote: Alexander Ypma (ASML)
11:00 - 11:50 Keynote: Alexander Ypma (ASML)
Title: Machine Learning challenges and opportunities in semiconductor manufacturing
Title: Machine Learning challenges and opportunities in semiconductor manufacturing
Bio: Alexander Ypma received a PhD degree from Delft University of Technology in 2001 on the topic Learning Methods for Machine Vibration Analysis and Health Monitoring. He continued on the topic of Bayesian Machine Learning and studied applications in web-mining, sales forecasting and audiology. After several research positions he moved in 2011 to lithography equipment manufacturer ASML, where he is currently leading a group of ~30 professionals in the area of Data Science & Data Engineering. Group activities include development of Predictive Maintenance applications, lithography performance optimization, Root Cause Analysis and Machine Learning Operations. He has contributed to 12 journal articles & book sections, over 20 conference publications, 2 popular magazine articles and holds 25 patents.
11:50 - 12:30 Three papers (10+2 mins each)
Nils Brockmann, Edward Elson Kosasih, Simon Baker, Iain Blair and Alexandra Brintrup. Supply Chain Link Prediction on an Uncertain Knowledge Graph
Maria Lua Nunes, Marília Barandas, Hugo Gamboa and Filipe Soares. Acoustic Structural Integrity Assessment of Ceramics using Supervised Machine Learning and Uncertainty-Based Rejection
Apostolos Giannoulidis, Nikodimos Nikolaidis, Athanasios Naskos, Anastasios Gounaris and Daniel Caljouw. Investigating thresholding techniques in a real predictive maintenance scenario
12:30 - 13:00 Poster & demo session
Papers with poster presentation
Surja Chaudhuri, Sheng-Yi Hsu, Hamideh Rostami, Anjan Prasad Gantapara and Mykola Pechenizkiy. Few-shot learning framework for fault classification and concept drift detection
Demo's
Florian Berton, Alexis Marion, Aurélien Lustrement, Patrick Ghosn, Pascal Crouzet, Ziad Zgheib and Clément Gautrais. Probe: An assistant for 3D parts process designers
Stefan Suwelack and Daniel Klitzke. The Data Curation Canvas – a hands-on approach to data-centric AI for manufacturing
Other posters that will be presented at the workshop
Yonghui Li, Hadi Seyedalizadeh Ara and Twan Basten. Model learning of timing constraints for intelligent cyber-physical production systems
Organization
Organization
Dimitra Gkorou (ASML), Pieter Van Hertum (ASML), Jefrey Lijffijt (Ghent University), Mykola Pechenizkiy (TU Eindhoven), Joaquin Vanschoren (TU Eindhoven), Michael Tiernan (Intel)
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