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Finding appropriate machine setting parameters in injection molding remains a difficult task due to the highly nonlinear process behavior. Artificial neural networks are a well-suited machine learning method for modelling injection molding processes, however, it is costly and therefore industrially unattractive to generate a sufficient amount of process samples for model training. Therefore, transfer learning is proposed as an approach to reuse already collected data from different processes to supplement a small training data set. Process simulations for the same part and 60 different materials of 6 different polymer classes are generated by design of experiments. After feature selection and hyperparameter optimization, finetuning as transfer learning technique is proposed to adapt from one or more polymer classes to an unknown one. The results illustrate a higher model quality for small datasets and selective higher asymptotes for the transfer learning approach in comparison with the base approach.

Different design of experiments (DoE) strategies for generation of injection molding process data and later usage as training database, e. g. for an artificial neural network substitute model, are investigated and compared. The objective is to find the most efficient and effective strategies for the modeling. The effects of six injection molding parameters on the length, width and weight of polypropylene plate specimen are simulated with different DoE methods from the following categories: full and fractional factorial designs, central composite designs, orthogonal Taguchi arrays, d -optimal designs and a space-filling design. The prediction performance, e. g. of the artificial neural networks, for unknown test data is evaluated. A 26−3 fractional factorial design including a center point is very efficient for this modeling task, whereas an inscribed central composite design is most effective. The artificial neural network with the latter experimental design as training data achieves a coefficient of determination R ² of 0.930 without a hyperparameter tuning to the specific data set.

Thin plasma polymers were applied on gold- and aluminium substrates using low pressure microwave- and radiofrequency-excited hexamethyldisilazane (HMDSN) plasma. The corrosion resistance properties of these coatings against sodium hydroxide solution (NaOH) was characterised by means of time resolved electrochemical impedance spectroscopy (EIS) and light microscopy. The evaluated resistance values were correlated with coating topography, chemical composition, wetting properties, and morphology with particular focus on porosity. Coating porosity was determined by using cyclic voltammetry (CV) and light microscopy. The topography and chemistry of the coatings were characterised by atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). The wetting properties were determined by optical contact angle (OCA) measurements. It is shown that the plasma polymer's resistance against NaOH can be greatly increased by lowering the energy input during the deposition process. This can be attributed to the strong correlation between porosity and resistivity: low energy input during plasma deposition leads to the formation of smaller and more uniform particles in the plasma bulk and possibly a Stranski–Krastanov growth of the layers, resulting in a smoother coating topography and lower nano-porosity. A more dense and compact coating morphology leads to a better corrosion protection performance.

Journal of CO2 utilization : JCOU 62, 102067 (2022). doi:10.1016/j.jcou.2022.102067, Published by Elsevier, Amsterdam [u.a.]

Polymer testing 104, 107393 (2021). doi:10.1016/j.polymertesting.2021.107393, Published by Elsevier Science, Amsterdam [u.a.]

The layer properties of plasma polymerized membranes produced in a microwave-excited PECVD process depend on the reactor properties, process characteristics and the properties of the substrate used. In order to be able to control gas separation properties for specific applications, thin silicon based SiOCH coatings were deposited on PDMS substrates. The influence of oxygen to monomer ratios and of microwave power input were investigated, as their variation in the process is generally known to have a significant influence on the formation of the layer structure. Correlations between process parameters, coating properties and gas separation or membrane performance were evaluated by permeation measurements, structure analysis (FESEM, AFM) and chemical analysis (XPS, FTIR). The investigations show a strong dependence of the membranes gas separation properties on the adjusted PECVD process parameters. It was possible to produce dense, ultra-smooth SiOCH coatings with ideal selectivities in the range of >40 for He/N2; 10 for He/CO2 and > 8 for CO2/N2.

Microstructure, as the connection between process and material properties in semi-crystalline thermoplastics, plays a crucial role in fabricating high-quality prats. Hence, it is essential to consider the microstructure by predicting the component properties. An integrative multi-scale simulation chain on an ICME platform was previously developed and successfully applied to predict the local, microstructure-dependant, effective elastic and thermal properties of an injection moulded plate from the isotactic polypropylene over its cross-section. However, the calculation time of several hours for small volume elements at the microscale seems to be an obstacle to employ it in real cases. Data-driven models, such as artificial neural networks are meant to be employed in the presented paper to solve this problem. The focus here is on the spherulitic microstructure of semi-crystalline microstructure predicted by the simulation in-house-developed software SphaeroSim as the link between solidification simulation and homogenisation. To build data-driven models parallel to these two simulation tools, the microstructure must be characterised, and meaningful features need to be extracted from it. This work aims to present general features for the characterisation of a spherulitic microstructure and build a data-driven model parallel to the solidification simulation, predicting the proposed features by a given cooling temperature history. A set of two-dimensional (surface area, circumference, Feret diameter, long Feret diameter, form factor, convex circumference, convexity, equivalent diameter and form deviation) and three-dimensional (volume, surface area, aspect ratio and sphericity) was calculated for a data set of about 500 simulations. Their distribution suggests that almost all of the spherulite have an ideally spherical shape. Therefore, some of the features can be replaced with each other. The achieved accuracies for each data-driven model relating to a predicted feature shows the great potential for substituting the original simulation tools for data-driven models, to immensely decrease the prediction time while keeping the high prediction accuracy.

The properties of plastic products can be optimized by a suitable design of the component surface. One promising method for plastics processing by injection molding is the use of molding tools structured in the micro-meter range. Within the scope of this paper, laser micro-structuring was carried out on two injection molds. A chromium-based nitride coating was deposited on one of the micro-structured mold by means of middle frequency magnetron sputtering (mfMS). Commercial plastics polycarbonate (PC2245) and polymethyl methacrylate (PMMA 7 N) were considered for all investigations. The coating contained xCr = 51 at.−% chromium, xAl = 30 at.−% aluminum and xN = 19 at.−% nitrogen exhibited a fine and dense columnar structure. It was experimentally seen that the coefficient of friction measured using a pin on disc tribometer reduces about 11% in case of PMMA 7 N, and about 17% for PC2245, using PVD. By comparing coated and uncoated surfaces, a lower wettability in contact with the plastics melt of PC2245 and PMMA 7 N analyzed by means of high temperature contact angle (CA) measurements was achieved for coated surfaces. This corresponds to the low amount of shear energy required for the separation of the solidified PC2245 and PMMA from the samples surfaces after the CA measurements. The influence of the temperature on coating property, roughness, after the CA measurements was observed as well. It was shown that the replication ratio of optical micro-structures can be increased significantly up to 20-30% by using a PVD coated in comparison to an uncoated mold.

Magnetic resonance imaging (MRI) is a powerful technique in materials science, in particular for the analysis of polymer and rubber materials. So far the use of this technique for quality control has not been fully explored mainly because of the prohibitive costs and maintenance associated with conventional MRI tomography systems. This constraint has been removed recently since robust and mobile desktop tomographs with permanent magnets have become available at reduced cost. In this work we apply an image processing chain algorithm to MR images of rubber profiles recorded with a desktop MRI scanner. Although the nominal spatial resolution of MR images is inherently lower than that of optical methods, we demonstrate that the digital resolution achieved after the image processing steps allows one to determine the spatial positions of the inner and outer contours with 50 μm precision. Using this information it is then possible to measure structural dimensions of the rubber profiles, such as wall thickness or internal voids, with precisions that are of the same order of magnitude as those observed with CT or camera imaging.

The freedom and potential gained by creating objects layer-by-layer using additive manufacturing technologies is offset by the limitations the 2.5D process holds. Currently, surface quality and mechanical properties of parts are limited by path planning algorithms. This study presents an algorithm for non-planar path planning with variable layer height, enabling the accurate representation of freeform surfaces and introducing the potential for increasing the parts’ mechanical properties by tailoring the layers to the load-case. By using mathematical functions to describe non-planar layers and calculating the amount of material to be extruded, layer thickness may vary inside the same layer, enabling transitions between different curved layers without introducing air gaps. In addition, means for selecting a beneficial nozzle geometry for non-planar additive manufacturing are presented. Finally, manufactured parts are evaluated, showing the benefits of the presented method. Specifically, it is shown that surface roughness can be reduced by 76% for curved top surfaces and indications for improved mechanical properties can be derived from performed tests.

The joining of fiber-reinforced plastics (FRP) currently poses particular process engineering challenges. Adhesive bonding or mechanical joining is normally used for such joints. However, bonding processes require complex measures for surface pre-treatment, fixing concepts and usually requires long curing times. On the other hand, mechanical joining processes such as screws or semi-hollow punch rivets lead to significant damage to the reinforcing fibers. Although different approaches for the production of plastic/metal hybrids are being pursued, there is still a need for a joining process that adequately meets the technical and economic challenges of joining metal and FRP. An innovative joining concept bypasses the problems of conventional joining techniques by using small-scale form-fitting elements in combination with established resistance welding processes. The investigations presented here include temperature measurements of the welds by means of contact thermocouples and analysis of the matrix material after welding by IR spectroscopy. The mechanical properties of the joint were verified in static shear tensile tests on coupon samples and in 3-point bending tests on geometries close to the component. The investigations carried out so far show high static bond strengths, which can be increased by coordinated welding parameters and component geometries. The joining process offers many possibilities with regard to the design freedom of the joining zone, since the pin structures can be flexibly adapted with regard to their arrangement, number and geometry, so that different requirements can be met. The Multi-Spot-Joint generates a quasi-ductile post-break characteristic. Thermal damage to the plastic matrix can be avoided by the targeted use of particularly short resistance welding processes. No damage to the plastic matrix could be detected during the IR spectroscopy.

The measurement of the temporal and local true strain behavior of polymer materials is important for the advancement in the sector of crash simulation of plastics parts. To simulate the strain rate dependent plastic material behavior of polymers under impact conditions using FEA (Finite Element Analysis), true stress/strain-curves at different constant strain rates are required as input data. A new approach for the measurement of true stress/strain-curves at constant strain rates is presented in this paper. The approach is based on a time based correlation method and works completely without using FEA based optimization procedures like inverse analysis. It only uses data measured in mechanical testing to almost automatically generate true stress/strain-curves at different constant strain rates.

Existing technologies for polyurethane (PU) foaming in discontinuous moulding processes show several disadvantages regarding the achievable foam properties like a limited flexibility of lightweight flexible foams. In contrast, the use of carbon dioxide (CO2) as a physical blowing agent offers advantages regarding its inert properties. But up to now, it was not possible to use CO2 for lightweight foams, because high amounts of CO2 lead to an uncontrolled foaming process. Therefore, a new physical foaming technology for moulded PU foam has been developed at IKV in order to enable high amounts of CO2 (up to 10 wt.-%) as a blowing agent. A gas counter pressure inside the mould cavity enables the precise control of the physical foaming process. For this reason, the mould technology as well as the high-pressure metering machine were adapted for the processing of highly loaded reaction mixtures with solved CO2. Using the new foaming technology, a density of 116 kg/m³ was achieved for rigid foams. In case of flexible foams, it was possible to reduce the density to 61 kg/m³. In comparison to conventional foaming using water as a blowing agent, the compressive strength is reduced to less than 30%, enabling the production of “softer” foams. At the same time, a high quality of the form filling behaviour, competitive to conventional foaming methods, was proven in test series with flow obstacles. Conclusively, the new foaming technology offers a new degree of freedom in adjusting the hardness of lightweight flexible foams and shows a high potential as substitution of physical blowing agents in order to reduce ecological concerns for the foaming of polyurethanes.

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 morphology and the tensile properties of unreinforced and short carbon fibre (SCF) reinforced Nylon 6/multiwalled carbon nanotube (MWCNT)-composites are investigated. The morphology analysis shows that MWCNT and SCF are randomly oriented in the composites. Furthermore, the SCF fail due to fibre pull-out, while the MWCNT fail due to fracture. Young's modulus and tensile strength of SCF reinforced Nylon 6 and Nylon 6/MWCNT-composites increase with increasing total filler volume content. Replacing SCF by MWCNT further enhances Young's modulus and the tensile strength. An additive modelling approach leads to better results at low MWCNT-volume contents, while at higher MWCNT loadings a multiplicative modelling approach results in a better approximation of the experimental data. Thus the SCF reinforced Nylon 6/MWCNT-composites behave at low MWCNT-volume contents like a polymer composite containing two different types of fillers, while at higher MWCNT loadings a behaviour of a short fibre reinforced nanocomposite is observed.

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.

The interaction between hygroscopic surfaces and plasma processes has exemplarily been examined for polyamide 6 (PA6). The water absorption of PA6 significantly influences the plasma processes and thus the resulting surface properties. In a first step the treatment of PA6 in oxygen plasmas was investigated. In etching processes moist surfaces become rougher than dry substrates. They release more water to the vacuum which can be detected by means of OH emission. In a second step PA6 substrates were coated in down-stream plasmas. Plasma polymerisation with HMDSO plasmas is also affected by hygroscopic surfaces. The chemical composition of the coating is influenced by the conditioning state of the substrate and more SiO-bonds are formed in the presence of water.