In predictive engineering for polymer processes, the rheological data is the most important data to end up with good prediction of processing parameters. In case of materials which are highly temperature sensitive and have a low bulk density, one has to be sure that the obtained data is representative for the future processing. One should avoid applying unrealistic conditions to the material causing unacceptable degradation of the material. To cover this issue, an advanced capillary rheometer has been developed which is able to heat the material to be tested in an advanced way. Simply conductive heating is combined with some controllable shearing resulting in measurement times which are only some minutes. Using a standard capillary rheometer, measurement times are most often more than ten minutes. The main disadvantage of this fast measuring technique is the sample temperature. To illustrate the good functioning of this equipment together with the validity of the results, a comparative reference measurement is set up for a non thermal sensitive material. This approach also allows to investigate the influence of the different settings influencing the shearing within the sample preparation for the shear viscosity measurement. Based on these promising results, the advanced rheometer can be used to perform accurate measurements for thermal sensitive materials as there are PVC. PVC is typically provided in powder form as raw material. While processing this material, it is highly sensitive for slip at the wall. Some promising results are obtained using this equipment.

Within polymer processing, nowadays, one has to deal with higher variations in material properties, for sure if one deals with recycled thermoplastic materials. Those waste streams typically can be of the same polymer type, but different products and or applications. To end up with a as homogeneous as possible material, typically solid mixing of the different batches is performed at large scale. Depending of the application and origin of the material, there is still a possibility to cope with larger variation within material properties. The most important material property for standard polymer processing as injection moulding or extrusion is the shear viscosity behavior in a large range. Within this investigation, at first, a strategy is developed to identify this variation in an industrial way. Next, a strategy is developed to use this characterized material data within a 1d approach valid for several types of the extrusion process. To end up with a physical reliable numerical tool coping with stochastics within data, there is a need to identify a correlation as function of time within the characterization of the shear viscosity. Within the process simulation, this correlation time is also used to implement stochastic information in a physically relevant way. This investigation can also be seen as a multiscale approach, as material characterization is done at meso scale; on processing scale (macro scale), local stochastic changes are compensated within the processing. In this investigation, the comparison is made between the processing of virgin material with the processing of recycled material. Finally, the potential of this approach is shown in a conceptual way.