Conference location

Organized by

13th Forming Technology Forum Zurich 2020

Forming technologies on the transformation path from virtual processes to smart and deep learning

methods

May 26 & 27, 2020Zurich, Switzerland

CALL FOR PAPERS

Form

ing

Tech

nolo

gy F

orum

Prof. Dr. P. Hora

Prof. Dr. W. Volk

Prof. Dr. A.H. van den Boogaard

swddrgSwiss Group of IDDRG

GDI Gottlieb Duttweiler InstituteLanghaldenstrasse 21CH-8803 Rüschlikon/Zürichwww.gdi.ch

Deep Learning Surface Defect Detection System

Conference focus

Intelligent Process Behavior Analysis

Eddy-Current Measurement System with Intelligent Process Analysis

0.05 0.058 0.066 0.074 0.082 0.09

Friction [-]

-5

-1

3

7

11

15

x-Bl

ank

[m

m]

DLdeep

learning

MLmachinelearning

AIartificial

intelligence

NMnetworkedmachines

DTdigitaltwin

materialmodel FEM

Topics General informationConference goals

During the two-day conference, the following topics will be discussed

I: Potentials and weaknesses of artificial intelligence and deep learning (DL) systems - Solving the problem of small data sets - DL vs. classical machine learning - Data generation using FEM

II: Experiments with self-learning evaluation methods - Eddy current based measurement of material

properties - Evaluation of nonlinear strain path influences

on FLC - Validation of yield locus models

III: Digital best fit constitutive models - Selection of best fit yield loci - Validation of normality rules - Implementation of complex constitutive models

IV: Development of digital twins - Virtual description of complex forming processes - Influence of stochastic parameters - Metamodeling techniques - Visualization of process limits

V: Digital assistant for the real tryout - Twin-based prediction of best practice tool

correction strategies - Prediction of sensitivities - Best selection of hardware components - Control strategies for smart processes

VI: Self-learning quality control - Optical detection of surface defects

General informationPaper lengthmax. 6 pages

Presentation length25 minutes including discussion

Important datesNovember 30, 2019 Abstract submission deadlineJanuary 31, 2020 Notification of acceptanceMarch 16, 2020 Final paper submission deadlineApril 5, 2020 Participants registration deadlineMay 26 & 27, 2020 13th Forming Technology Forum Zurich

Conference feesIndustry EUR 650Academics EUR 400Speakers EUR 350(incl. catering during the conference days & dinner on May 26)Early bird discount EUR 50 for registrations before February 29, 2020.

Conference languageEnglish

Exhibition and sponsoringWe have exhibition space available. Please contact our administration for further information.

Administration and contactMs. Carole HaerryPhone +41 44 632 26 10Fax +41 44 632 11 65Email ftf@ethz.ch

RegistrationFor more information please visit our website:www.ivp.ethz.ch

ChairProf. Dr. P. Hora

Prof. Dr. W. Volk

Prof. Dr. A.H. (Ton) van den Boogaard

Forming technologies on the transforma-tion path from virtual processes to smart and deep learning methods

For years, the forming technology community has been a successful pioneer in the field of numerical process simula-tions. To date, the virtual validation of processes integrated as a standardized step into the planning process was hardly used to such a large extent in any other manufacturing field. For this reason, many of the terms declared by Industry 4.0 as the future in manufacturing technology have already been continuously implemented in forming technology pro-cesses.

Artificial intelligence methods, based for example on deep learning algorithms, offer a completely new approach little known in manufacturing technologies. Compared to the often-used «exact sciences» in classical engineering, these methods represent an entirely new numerical approach. Thus, the vision is to develop tools with «artificial intelli-gence» as well as «self-learning systems» to be integrated into the manufacturing and planning process.

The conference will highlight the latest state of research of these technologies based on selected examples in the fields of «self-learning smart experiments», «self-correcting tools» and «self-learning quality control» as well as in other possible future domains.

Nevertheless, the classical numerical methods such as used by FEM programs will continue to be indispensable in the future. Therefore, the conference sessions « Digital best fit constitutive models » and «Development of digital twins» will focus on the latest developments in these classical nu-merical fields.

Prof. Dr. P. Hora