Shifting Focus to Quality: An Innovative Modeling Approach Includes Processing History for Rubber Part Quality Simulation.

An innovative modeling approach for the simulative description of the part quality of rubber materials, including the processing history, is presented in this paper. This modeling approach, the so-called average curing speed (ACS) model, is based on the degree of cure and the average curing speed instead of the conventionally considered temperature approach. Such approach neglects the processing history by calculating only the degree of cure. Thus, the correlation with part quality has to be performed either after the simulation or with the aid of other numerical analysis programs. Instead, by applying the ACS model, the key advantage is that the processing history is already taken into account during the filling and curing simulation, demanding a single calibration step with quality information to be able to calculate the part quality. For this purpose, parts were manufactured at mold temperatures ranging from 140 °C to 170 °C and degrees of cure from 24% to 99% via compression molding and subsequently the permanent deformation, i.e., the compression set (CS), of each part was analyzed. The CS results show that one and the same degree of cure; for example, 80%, which was defined on the basis of reaction isotherms, causes an almost twofold higher CS value for parts manufactured at 170 °C. Consequently, considerable deviations may occur when real part qualities are correlated with degrees of cure from simulations with common state-of-the-art kinetic models. By applying the ACS model, it was demonstrated that this challenge could be solved. Parts manufactured by compression molding exhibited the same quality as those simulated with the ACS model. Finally, this innovative modeling approach (fully implemented in the SIGMASOFT v6.0 simulation routine) provides enormous potential for understanding local differences in the quality of rubber parts, being an ideal tool for optimizing rubber parts through simulation routines.