2022 AI for Manufacturing (AI4M) Workshop
Hosted by DAAAM International Symposium, Vienna, Austria
October 26, 2022, Virtual
Focus
Methods and Approaches for AI4M Economic Impact of AI4M Accountability and Explainability of AI4M Security Challenges in AI4M
Links & dates
1) Registration: Link
2) Paper template: Link
3) Paper submission: Link
4) Fees: Link
Submission deadline: 21st October 2022
Hosted by
This is a workshop of the DAAAM International Symposium, which will take place 24th to 28th October, virtually. The workshop will take place on Wednesday 26th October, 09:00 – 11:00 CEST.
Introduction
AI is one of the pillars of the Industry 4.0 concept and recent advances in underlying AI technologies including computer vision, robotic control, machine learning and decision support, have all been included into major changes in manufacturing plants. This workshop seeks to bring together researchers from both technical and social disciplines to present their current and future work and discuss the issues needing interdisciplinary and/or international cooperation to maximise the potential of AI in Manufacturing in a way that will benefit not just manufacturing companies’ profitability and competitiveness, but improve worker safety, reduce environmental impact, and improve (or at least not worsen) social issues such as economic inequality and corporate accountability.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. Papers can range from short conceptual analyses to description of working systems. Papers presented at the workshop should focus not just on presenting a specific research result (technical solution of a problem, economic analysis of the impact of a particular technology) but should seek to place such detailed results into the broader context of the development of AI for Manufacturing or the consequences and potential policy implications of a specific technology or social/economic issue. Ethical issues such as ensuring explainability, legal issues such as ensuring suitable accountability, economic/social issues such as the impact of increased automation in manufacturing and changing workforce expectations and economic return for workers should be considered where appropriate. The limits of current technological developments and suitable directions for future research should be included in papers describing current technical advancements. Papers submitted to the workshop should be 6-15 pages, including list of references. They should be formatted following the DAAAM paper template.
Suggested List of Topics (non-exhaustive)
- AI Methods and Approaches for Manufacturing
- Research Challenges in AI for Manufacturing
- The Economic Impact of AI in Manufacturing
- Accountability and Explainability for AI in Manufacturing
- Major new technical developments in AI for Manufacturing and remaining challenges
- Security Challenges of and Applications for AI in Manufacturing
Organizing committee
The workshop is organised by partners in the EU Horizon 2020 project EU-Japan.AI (This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957339.)
- Dr Andrew A. Adams, Centre for Business Information Ethics, Meiji University, Tokyo, Japan 🇯🇵
- Dr Damir Haskovic, MINDS & SPARKS, Vienna, Austria 🇪🇺
- Dr Matej Kovacic, Jozef Stefan Institute, International Research Centre on Artificial Intelligence, and University of Nova Gorica, Slovenia 🇪🇺
- Prof Akio Takemoto, Institute for the Advanced Study of Sustainability, United Nations University, Tokyo, Japan 🇯🇵
Programme Committee
- Programme Chair: Dr Andrew A. Adams, Meiji University, Japan 🇯🇵
- Professor retd Dr.sc. Dr.mult.h.c.Prof.h.c. Branko Katalinic 🇪🇺
- Dr Marc Anderson, INRIA, France 🇪🇺
- Prof Christian Beecks, Fern Universität in Hagen, Germany 🇪🇺
- Dr. Sisay Adugna Chala, Fraunhofer Institute for Applied Information Technology, Germany 🇪🇺
- Dr Marko Grobelnik, Jozef Stefan Institute, Slovenia 🇪🇺
- Dr Damir Haskovic, MINDS & SPARKS, Austria 🇪🇺
- Dr Upalat Korwatanasakul, The United Nations University Institute for the Advanced Study of Sustainability, Japan 🇯🇵
- Prof Kiyoshi Murata, Meiji University, Japan 🇯🇵
- Mr Jože Rožanec, Jozef Stefan Institute, Slovenia 🇪🇺
- Prof. Damir Godec, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia 🇪🇺
Supported by