Topics

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

  1. 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
  2. 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
  3. Digital best fit constitutive models
    • Selection of best fit yield loci
    • Validation of normality rules
    • Implementation of complex constitutive models
  4. Development of digital twins
    • Virtual description of complex forming processes
    • Influence of stochastic parameters
    • Metamodeling techniques
    • Visualization of process limits
  5. 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
  6. Self-learning quality control
    • Optical detection of surface defects