AI for Manufacturing Workshop 2023

co-located with ECML-PKDD

Friday 22 September 2023 – 14h30-18h – PoliTO Rooms I (2i)

Co-located with the ECML PKDD 2023, Turin (Italy)

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: 


Keynote: Gianpiero Negri (Amazon)

The goal of this talk is to provide an introduction on Amazon Mechatronics and Sustainable Packaging (part of Amazon Global Robotics) organizational structure and scope, and to provide an overview of some main AI/ML potential applications to Mechatronics Product Development process, with a main focus on the safety and compliance/standardization aspects, available norms and policies, and what’s outstanding to tackle the future technical and operational challenges in complex manufacturing and logistics environment.

Panel: Robustness & safety for AI in Manufacturing

Panel speakers: Anjan Prasad Gantapara (ASML), Gianpiero Negri (Amazon), Sławomir Nowaczyk (Halmstad University)



14:30 - 15:35 Contributed Papers

Reinforcement learning for segmented manufacturing. Nathalie Paul (Fraunhofer IAIS) et al.

Towards reducing data acquisition and labeling for defect detection using simulated data. Lukas Malte Kemeter (Fraunhofer IIS) et al.

Automatic tool wear inspection by cascading sensor and image data. Robbert Verbeke (Sirris) et al.

Applying machine learning models on metrology data for predicting device electrical performance. Bappaditya Dey (imec) et al.

Identifying contributors to manufacturing outcomes in a multi-echelon setting: a decentralised uncertainty quantification approach. Stefan Schoepf (U Cambridge) et al.

Comparing deep reinforcement learning algorithms in two-echelon supply chains. Francesco Stranieri & Fabio A Stella (U Milano-Bicocca)

15:35 - 16:00 Keynote Gianpiero Negri

16:00 - 16:30 Break

16:30 - 17:10 Panel Robustness & safety in AI for Manufacturing

Jefrey Lijffijt (Ghent University), Dimitra Gkorou (ASML), Pieter Van Hertum (ASML), Manuel Giollo (Amazon), Mykola Pechenizkiy (TU Eindhoven)

Program Committee Members

Twan Basten (TU Eindhoven)

Bappaditya Dey (imec)

Clément Gautrais (BrightClue)

Edith Heiter (Ghent University)

Steven Latré (imec)

Konstantinos Papangelou (ASML)

Kai Puolamäki (University of Helsinki)

Michael Tiernan (Intel)

Mathias Verbeke (KU Leuven)