Due to the high complexity of the foaming technology, the relationship between processing and final properties of parts produced is not completely understood. Investigating the causality chain Processing–Morphology–Properties is of great importance, especially for the automotive industry, in order to be able to tailor the mechanical properties of foamed parts. This article examines and qualifies the effects of seven process parameters (melt/mold temperature, degree of foaming, injection speed, delay time, gas content, and back pressure) on biaxial bending and flexural behavior—the predominant deformation mechanisms in interior automotive applications—of foamed plaques, using the MuCell process. The results clearly show that three major factors (mold temperature, degree of foaming, and delay time) have significant impact on the mechanical properties of the foamed parts. For a clear understanding of these interactions, computed tomography scans of certain plaques are correlated to process parameters and mechanical performance. This article should forge a bridge between production and performance. © 2018 The Authors. Journal of Applied Polymer Science published by Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47275.

In terms of sustainability, injection foam molding gains in importance. Yet still many questions throughout the whole process remain unanswered. Especially, the conditions inside the cylinder during gas injection are fraught with uncertainty. Our development of a new methodology for the determination of dynamic solubility in injection foam molding helps to answer the most basic question regarding gas loading: Using the bulk modulus of the polymer–gas mixture, the dynamic solubility limit can be detected. In a first series of tests, the methodology was verified with simultaneous ultrasonic measurements—an excellent agreement was observed. In this work, a second, more thorough test series is presented. Using the bulk modulus methodology on different polypropylene grades, dynamic solubility limits between 0.62 and 2.56 wt% nitrogen at pressures between 80 and 200 bar and a temperature of 230°C were determined directly on an injection molding machine. The detailed theoretical background for this technique, as well as a mathematical automation approach, is provided. This innovative yet simple method yields novel insights on process limits and provides the possibility of an a priori machine setup or a fully automatic self‐adjustment of the machine. POLYM. ENG. SCI., 60: 330–340, 2019. © 2019 The Authors. Polymer Engineering & Science published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineers.

The importance of foam injection molded components in industrial applications increases, above all driven by sustainability concerns. In practice, their applicability almost exclusively depends on their mechanical behavior, which is still difficult to predict based on their microstructure. This work aims to present an approach based upon phenomenological observations. From a processing perspective, the objective is to describe the direct processing‐properties‐relationship. Therefore, this work focuses on the effects of different processing parameters on selected final mechanical properties of foam injection molded components using glass fiber‐reinforced polypropylene. A full factorial, central composite design allows for the detection of nonlinear effects, the application of response surface methodology, and the creation of contour plots. Considering three important process parameters (mold temperature, degree of foaming, delay time) and—for the automotive industry—highly important mechanical properties in bi‐ and uniaxial bending, the results show a detailed picture of individual dependences, but also two‐dimensional interactions between the different process parameters. Improvements of more than 140% in absorbed energy and flexural stiffness were obtained at constant part weight. Modulus and strength were increased by 37 and 44%, respectively.

We present a novel measurement die for characterizing the flow behavior of gas-containing polymer melts. The die is mounted directly on the injection-molding cylinder in place of the mold cavity and thus enables near-process measurement of viscosity (i.e., under the conditions that would be present were a mold attached). This integration also resolves the issue of keeping gas-containing polymer melts under pressure during measurement to prevent desorption. After thermal characterization of the die, various correction approaches were compared against each other to identify the most suitable one for our case. We conducted measurements using polypropylene in combination with two different chemical blowing agents. Increasing the blowing-agent content to up to 6% revealed an interestingly low influence of gases on melt viscosity, which was confirmed by elongational viscosity measurements. For verification, we compared our results to corresponding measurements taken on a high-pressure capillary rheometer and found that they were in excellent agreement. Our die cannot only be used for rheological characterization. Combined with ultrasound sensors, it provides an innovative way of measuring the volumetric flow rate. This development represents an important step in improving the sustainability of gas-containing polymer processing.

Inspired by the Industry 4.0 trend towards greater user-friendliness and self-optimization of machines, we present a novel approach to reducing backpressure in foam injection molding. Our method builds on the compressibility of polymer-gas mixtures to detect undissolved gas phases during processing at insufficient backpressures. Identification of a characteristic behavior of the bulk modulus upon transition from homogeneous to heterogeneous polymer-gas mixtures facilitated the determination of the minimum pressure required during production to be determined, as verified by ultrasound measurements. Optimization of the pressure conditions inside the barrel by means of our approach saves resources, making the process more sustainable. Our method yielded a 45% increase in plasticizing capacity, reduced the torque needed by 24%, and required 46% less plasticizing work and lower pressures in the gas supply chain. The components produced exhibited both improved mechanical bending properties and lower densities. From an economic point of view, the main advantages of optimized backpressures are reduced wear and lower energy consumption. The methodology presented in this study has considerable potential in terms of sustainable production and offers the prospect of fully autonomous process optimization.

There is still uncertainty concerning processes and conditions inside the cylinder during gas injection in injection foam molding. Apart from static solubility and its measurement, determination of dynamic solubility is of great interest for the operator in order not to overload the melt. Our development of a novel measurement method makes the detection of the ultimate limit of solvable amount of gas at certain process conditions prior to production possible, using the compression modulus of the gas-polymer-solution in a MuCell®-process. The method is based on the fact that the compressibility of a polymer-gas-solution beyond its solubility limit (i.e. under presence of a second, discrete gas phase) drops sharply. Based on three different versions of a polypropylene homopolymer dynamic solubility measurements at different pressures were carried out. Depending on material formulation and process conditions dynamic solubility limits between 0.6 wt% and 3.6 wt% nitrogen were measured. For verification of the obtained results, ultrasonic measurements were conducted simultaneously. Excellent agreement between the two methods was observed. For the whole test procedure, a measurement flange was used. However, it could be shown that the compression modulus can also be determined without any additional equipment. This simple yet innovative method yields new insights in terms of process limits and conditions inside the barrel. Future developments should include the fully-automatic self-adjustment of the machine.