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Daten uber die Produktion sowie die umliegenden Felder der Wertschopfungskette gewinnen in der Kunststoffverarbeitung immens an Bedeutung. Einerseits sind Informationen in Form von quantitativen Daten die Grundlage fur jegliche Verbesserung einer Produktion sowie der organisatorischen und logistischen Aufgaben, die dafur notwendig sind. Andererseits haben sich sowohl Datenerfassungsmethoden sowie Datenverarbeitungsmethoden weiterentwickelt, sodass sie effizienter und preiswerter eingesetzt werden konnen und somit der Nutzen aus Daten in den Vordergrund tritt. Im Folgenden wird auf drei wichtige Bereiche in der Kunststoffverarbeitung eingegangen, durch die Daten einen Mehrwert generieren, der einerseits direkte sowie indirekte Monetarisierungsmoglichkeiten generiert. Nach einer Einordnung wird dies anhand von digitalen Dienstleistungen veranschaulicht, die auf der Verfugbarkeit von Produktionsdaten aufbauen und ein neues Geschaftsfeld eroffnet haben. Ein weiterer wichtiger Aspekt stellt ein Marktsegment dar, dass sich auf die Beschaffung von Daten, insbesondere von Produktionsdaten ausrichtet. Ein enormes Potenzial bietet hierbei die Bereitstellung von Hardware, Software sowie damit verbundenen Dienstleistungen zur Erfassung von Maschinen- und Produktionsdaten. Zuletzt wird auf moderne Methoden eingegangen, die einen indirekten Monetarisierungseffekt bewirken, indem sie Produktionsumgebungen optimieren und effizienter gestalten. Somit nehmen sie einen positiven Einfluss auf die Wirtschaftlichkeit des Unternehmens.

One of the largest challenges in production using melt-based processes is the manufacturing of precise parts. Especially due to high differences in temperature of the produced parts while processing, shrinkage cannot be avoided, since the processing material is typically heated up, molded and cooled down. In injection molding, the molten plastic is loaded by high variations in temperature and pressure while being processed. The gradients can lead to a significant change of the local specific volume, shrinkage potential and inner stresses, which can result in part warpage. In order to increase the precision of the manufactured parts, the shrinkage potential has to be homogenised to achieve an even shrinkage and therefore minimise part warpage. In this work, the approach for homogenisation of the shrinkage potential is a homogenisation of the specific volume and density respectively. Pursuing the goal of a homogeneous distribution of the specific volume leads to manipulation of the influencing factors namely temperature and pressure. The impact of temperature and pressure changes on the specific volume can further be quantitatively described by the material specific pvT-data. Based on geometric restrictions, a manipulation of the local pressure inside the cavity in most cases is impossible. However, on the other hand, a local control of the temperature is possible using highly dynamic tempering techniques. Based on this line of arguments, the paper describes the development of a highly segmented dynamic temperature control in injection molding to locally influence the mold and part temperature. Thereby, the specific volume of the part will be locally adjusted to reduce warpage as well as to compensate process variations occurring by changing material properties or varying ambient conditions. Due to the nature of thermal processes a special control strategy has to be developed to enable accurate temperature control, which is able to compensate slow thermal reaction in a highly dynamic process.

Digital Twins (DTs) of Cyber-Physical Production Systems (CPPSs) enable the smart automation of production processes, collection of data, and can thus reduce manual efforts for supervising and controlling CPPSs. Realizing DTs is challenging and requires significant efforts for their conception and integration with the represented CPPS. To mitigate this, we present an approach to systematically engineering DTs for injection molding that supports domain-specific customizations and automation of essential development activities based on a model-driven reference architecture. In this approach, reactive CPPS behavior is defined in terms of a Domain-Specific Language (DSL) for specifying events that occur in the physical system. The reference architecture connects to the CPPS through a novel DSL for representing OPC-UA bindings. We have evaluated this approach with a DT of an injection molding machine that controls the machine to optimize the Design of Experiment (DoE) parameters between experiment cycles before the products are molded. Through this, our reference implementation of the DT facilitates the time-consuming setup of a DT and the subsequent injection molding activities. Overall, this facilitates to systematically engineer digital twins with reactive behavior that help to optimize machine use.

High precision, warpage free injection molded parts are highly in demand despite posing a great challenge. According to the pvT-behavior of the polymer, local variations of temperatures and pressures lead to inhomogeneous shrinkage which results in warpage. Since the pressure is dependent on the flow path, a homogenization of the specific volume is aimed by controlling the local mold temperatures. Therefore, a mold with 18 individually controllable tempering zones was developed, each zone equipped with ceramic heating elements and liquid CO2 expansion chambers. Due to the high mass of the mold, thermal processes underlie significant delays. The precise actuation of the tempering zones therefore requires a suitable control strategy. Two control strategies for the tempering zones were investigated on a basis of experimental trials. The tempering zones were initially controlled by a PID controller since it is easy to use and has low hardware requirements. To yield superior control precision, a model predictive control approach (MPC) has been recently developed and implemented, based on a discretized one-dimensional Fourier heat equation. The control accuracy of both control strategies was tested with an asymmetrical mold tempering experiment, which showed that the MPC is far more precise than the PID control approach.

During the injection moulding process, local differences in pressure and temperature lead to different shrinkage over the part. This inhomogeneous shrinkage can lead to internal stresses, which are compensated by an undesirable warpage of the part. A sophisticated design of the cooling channels can avoid most of these problems. In previous research, it was shown that a locally adjusted temperature distribution on the cavity surface leads to less warpage of the part. In order to achieve this temperature distribution, an adapted cooling channel design is necessary. This design process is not possible with an analytical calculation but is the result of an iterative and numerical optimisation process. In this paper, a simulative approach for an automatic cooling channel layout via an inverse heat conduction problem is presented. Based on previous results, the methodology is adapted to three-dimensional problems. This approach brings the local heat and cooling demand of the part in equilibrium based on the postulate of a locally homogeneous material density. By this methodology, a proper cooling channel design close to the mould surface is determined. Simulations show a significant reduction of warpage by at least 22 % which will be validated by experimental results.

Mold filling is an injection molding stage of great significance, because many defects of the plastic components (e.g. weld lines, burrs or insufficient filling) can occur during this process step. Therefore, it plays an important role in determining the quality of the produced parts. Our goal is the temporal refinement in the vicinity of the evolving melt front, in the context of 4D simplex-type space-time grids [1, 2]. This novel discretization method has an inherent flexibility to employ completely unstructured meshes with varying levels of resolution both in spatial dimensions and in the time dimension, thus allowing the use of local time-stepping during the simulations. This can lead to a higher simulation precision, while preserving calculation efficiency. A 3D benchmark case, which concerns the filling of a plate-shaped geometry, is used for verifying our numerical approach [3]. The simulation results obtained with the fully unstructured space-time discretization are compared to those obtained with the standard space-time method and to Moldflow simulation results. This example also serves for providing reliable timing measurements and the efficiency aspects of the filling simulation of complex 3D molds while applying adaptive temporal refinement.

The process dependence of pressure-specific volume-temperature (pvT) measurement for an amorphous polymer, acrylonitrile-butadiene-styrene (ABS), was investigated. The influences of different measurement processes (heating, cooling, compression, and decompression with different rates) were considered in the pvT measurements. The pvT measurements of isobaric cooling and heating with different cooling and heating rates (2, 5, and 10 °C/min) and isothermal compression and decompression with different compression and decompression rates (up to 920 bar/s) were conducted. The testing temperature ranged between 40 and 230 °C and the pressure ranged between 20 and 2200 bar. The obtained results demonstrated that the pvT diagram will be significantly different depending on the direction in which the pressure or temperature is changing and also on the rate of the change. Isobaric pvT diagrams are different between cooling and heating. Fast cooling accelerates phase transitions, while fast heating reverses. Specific volume at the same pressure and temperature in decompression process is lower than that in compression. Compression and decompression leads to different pvT curves. Compression and decompression rates have different effects on specific volume in different states.

The pressure-specific volume-temperature (pvT) relationships of polymers are basic data for polymer engineering and polymer physics. The specific volume (vsp) is not only defined by the current value of pressure (p) and temperature (T) but is also dependent on the process history of p and T. The influence of measurement processes on the pvT relationships of a semi-crystalline polymer, polypropylene (PP), has been studied using a piston-die pvT testing device. Based on the isobaric cooling/heating processes and the isothermal compression/decompression processes, the specific volume was examined as a function of cooling, heating, compression, decompression, cooling/heating rates and compression/decompression rates. The specific volume increases with increasing cooling rates in the crystallization and solid state, and decreases with increasing heating rates in the crystallization and molten state. The decompression process causes lower specific volume than the compression process. The specific volume decreases with increasing compression rates but decreases then increases with increasing decompression rates.