Improved modeling for the reheat phase in thermoforming through an uncertainty treatment of the key parameters

This work focuses on the treatment of parameter uncertainty in the simulation of the sheet reheat phase of the thermoforming process. The approach aims to improve the quality of predictions through more accurate evaluation of the input parameters. First, the modeling approach is employed to perform a sensitivity analysis on the reheat phase. Then, a series of specialized experiments with heat flux and temperature sensors are performed on a thermoforming machine. The key parameters identified through the sensitivity analysis are the subject of these experiments. The natural convective heat transfer coefficients are evaluated by two different approaches. Through treatment of the uncertainty associated with the input parameters, the prediction of sheet reheat phase is significantly improved.