ECMI Webinar “Math for Industry 4.0 - Models, Methods and Big Data”

December 2 - 3, 2020


UPDATE, November 24, 2020: Preliminary schedule and list of presentations is available HERE

In a joint activity of the Special Interest Groups Mathematics for Big Data and Math for the Digital Factory of the European Consortium for Mathematics in Industry (ECMI) this workshop strives to bring together data scientists, mathematicians, and engineers from academia and industry to discuss recent developments in digital manufacturing. The workshop consists of a combination of plenary and contributed scientific talks. There will be a session on digital twin technology with presentations highlighting theoretical concepts and practitioners from industry showing state of the art digital twin realizations. Another topic will be machine learning and artificial intelligence applications in automated manufacturing. In addition, we plan a session with representatives of the MANUFUTURE technology platform and the EU Industrial Technologies Programme (NMP) about challenges in manufacturing research and funding opportunities in the new Horizon Europe framework program. Further topics to be discussed are (but not limited to)

  • Artificial Intelligence and Manufacturing
  • Automation and reinforcement learning
  • Discrete event systems, petri nets and workflow simulation
  • Distributed Optimization
  • Math for virtual product development
  • Modelling, simulation, and optimization (MSO) of production systems
  • Topological Data Analysis (TDA) in Machine Learning

Invited Speakers

  • M. Arnold (University of Halle-Wittenberg, Germany)
  • L. Bonilla (Universidad Carlos III de Madrid, Spain)
  • R. Bueno Zabalo (BRTA and Manufuture, Spain)
  • L. Burger/V. Dörlich (Fraunhofer ITWM Kaiserslautern, Germany)
  • A. Carpio (Universidad Complutense de Madrid, Spain)
  • F. Edelvik (Fraunhofer-Chalmers Centre for Industrial Mathematics, Gothenburg, Sweden)
  • L. Formaggia (Politecnico di Milano, Italy)
  • D. Hartmann (Siemens AG, Munich, Germany)
  • D. Jakovetic (University of Novi Sad, Serbia)
  • A. Jungiewicz (Siemens, Germany)
  • J. Korell/P. Wolny (PTKA, Germany)
  • P. Lünnemann (Fraunhofer IPK, Berlin, Germany)
  • V. Mehrmann (TU Berlin, Germany)
  • M. Sanarico (SDG Group, Italy)
  • B. Simeon (University of Kaiserslautern, Germany)
  • A. Strahilov (EKS InTec GmbH, Weingarten, Germany)

Call for abstracts

We welcome academics and practitioners to participate in this workshop and to submit an abstract for a contributed presentation on any aspect related to digital manufacturing & big data using the pre-registration form here.


Deadline for submission of abstracts was November 18, 2020.
Unfortunately, we cannot accept any further applications for talks.



Registration

Registration is done in a two-stage process. We ask everybody interested in the workshop to pre-register using the link below. During the pre-registration process you can also submit the abstract for a scientific presentation.


If you have been notified that your presentation has been accepted or if you are from an ECMI institution you are now officially registered and no further action is needed.

All other participants will have to pay the registration fee. They will receive an email with the link to make the payment.

All confirmed participants will receive the Zoom link for our webinar on December 1, 2020 together with the booklet including the book of abstract and the list of participants.


Please click here for pre-registration.

Registration fees

  • Speakers and participants from ECMI institutions:   Free
  • Everybody else:   50 €
Please note: Fee waivers are available on request for participants from developing countries (see list here) by sending an email to ma4difa@wias-berlin.de.


Every registered participant will receive a link to the event, a list of participants, the book of abstracts, as well as access to the slides of all presenters who agree to share their presentation.


Organizers

Support

Selfhtml


Contact and further information

E-Mail: ma4difa@wias-berlin.de
Phone: +49 30 20372-555