Injection molding of rubber compounds is an easily conducted yet sophisticated method for rubber processing. Simulation software is used to examine the optimal process conditions, identify failure scenarios, and save resources. Due to the complexity of the entire process, various aspects have to be considered in the numerical approach. This contribution focused on a comparison of process simulations with various definitions of the material’s inlet temperature, ranging from a stepwise increase, but constant temperature, to an exact axial mass temperature profile prior to injection. The latter was obtained with a specially designed, unique test stand consisting of a plasticizing cylinder equipped with pressure sensors, a throttle valve for pressure adjustments, and a measurement bar with thermocouples for the determination of the actual state of the mass temperature. For the verification of the theoretical calculations, practical experiments were conducted on a rubber injection molding machine equipped with the mold used in the simulation. The moldings, obtained at different vulcanization time, were characterized mechanically and the results were normalized to a relative degree of cure in order to enable comparison of the real process and the simulation. Considering the actual state of the mass temperature, the simulation showed an excellent correlation of the measured and calculated mass temperatures in the cold runner. Additionally, the relative degree of cure was closer to reality when the mass temperature profile after dosing was applied in the simulation.

Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part’s state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements.

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^® v$6.0$ 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.