Multilevel Methods for Quality Assessment of Injection Molding under Uncertainty

Doctoral Researcher
Name Role at KCDS
KCDS Fellow
KCDS Supervisors
Name Role at KCDS
SEE Supervisor
MATH Supervisor, member of the Steering Committee

Abstract

Since precision and reliability of plastic parts are crucial, it is necessary to understand and evaluate the effects of uncertainties, such as variations in material properties and process control. My research aims at the systematic modeling of risk measures using mathematical methods, in particular multilevel Monte Carlo techniques, to enable efficient quality assessment of injection molding processes under uncertainty.