CONNECT European Moldflow User Meeting 2024
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Agenda of CONNECT 2024
Dr. Janz Turk, HELLA GmbH & Co. KGaA, Moldflow Simulation Expert
Thermoelasticity of Injection-Molded Parts
In the realm of injection-molded parts, small length scale deformation defects such as sink marks often pose a major challenge to the aesthetics or functionality of the parts. To address this problem, we present a comprehensive thermoelastomechanical approach that calculates the deformation of injection molded plastic by solving the elastic problem at each time step. In our methodology, two treatments of the molten core are considered: one as a liquid and the other as a rubbery state. Our results suggest that the rubbery state treatment provides higher accuracy in predicting the deformation results, as it maintains the displacement of the localized thermal shrinkage in its vicinity. The validity of our method is supported by empirical measurements on produced parts from the existing literature as well as on samples that we molded independently.
Akash Castelino, Inpro, Software Development
twino: Extended productivity toolkit for ramp-up
Building on the presentation of twino at CONNECT 2023, this year inpro GmbH will present the results of the further development of twino as a productivity tool for the sampling, validation and inspection of injection molding parts and processes. Through operational use and critical feedback from initial customers, twino’s measurement and testing functions were sharpened and improved. In particular, the recording of shrinkage, even over a longer period of time and especially for large automobile parts, and the checking of “part completeness” as difficult, repetitive and time-consuming inspection processes have been expanded. In this presentation we will introduce you to twino as a practical digital solution that supports and improves your workflows in engineering, simulation, sampling and ramp-up processes and we will inform you about the market launch of twino together with MF Software.
Dr. Camilo Cruz, Robert Bosch GmbH, Research & Development
Uncertainty Propagation in Injection Molding Simulation – Tackling the Variability of Recycled Materials in Virtual Design
To fully deploy virtual validation of injection molded parts in the industrial context, we need to distribute professional tools for propagating the uncertainty of the design variables along the current simulation workflows. Today those simulation workflows are deterministic but do not estimate uncertainty, which is a natural feature in our physical world and is a key element in design for reliability. On top of that, the consideration of uncertainty appears to be particularly relevant when dealing with recycled materials, as there is a common concern about the higher variability of their properties.
We propose a virtual framework for propagating uncertainty in injection molding simulation by employing Autodesk® Moldflow® and an internal Python-based tool for metamodel generation/exploitation. To provide a concrete example, we consider the case of mechanically recycled short-fiber reinforced thermoplastics as raw material for injection molding. First, we discuss the actual variation of fiber length and shear viscosity of an in-house mechanically recycled glass fiber reinforced PBT. Subsequently, we showcase a virtual workflow for transporting the uncertainty of those material properties in the estimation of fiber orientation, which is a pivotal input for the computer-assisted anisotropic mechanical design. Finally, we present an outlook to the software tooling that could be implemented for propagating the uncertainty further until the structural simulation domain.
Dr.-Ing. Julian Heinisch, LG Chem Ltd., Injection Molding Engineer
Handling batch variations in Post-Consumer Recycled PC/ABS
Post-Consumer Recycled (PCR) plastic materials will play a crucial role in order to fulfill the objectives of the upcoming End of Live Vehicle Regulation by the EU. According to this regulation 25% of plastics to build new vehicles must be recycled.
With sufficient experience in material sourcing and quality control of source material and final compound, PCR materials can be compounded to a virgin-like quality. However, uncertainty surrounding the quality of PCR materials often leads to reluctance in their application.
In this presentation, we take a look at batch variations of fossil-based PC/ABS and PC/ABS with 50% PCR content in comparison. An approach to estimate the effects of different batches early in the design phase with Moldflow is suggested based on the variations. The objective is to evaluate how the quality of PCR materials impacts quality criteria such as the dimensional accuracy of a part and to provide a range of expected variations. Ultimately, the designer shall be enabled to make more informed decisions when selecting sustainable materials.
Prof. Dr. Thomas Lucyshyn, Montanuniversität Leoben
Extending the simulation capabilities of Moldflow with Synergy API and Python using the example of film back injection molding
Moldflow already offers many calculation options for various special processes, but there are often special aspects that cannot be simulated in the standard version. However, the Synergy API opens up enormous potential for advanced users to expand the simulation options themselves. This presentation will show how the Synergy API and custom Python scripts can be used to implement a damage mechanism for film back injection molding of a multi-layer film. For this purpose, existing results (temperatures, shear stresses) were exported from Moldflow and used in Python scripts for a proprietary empirically developed formula, which correlated the occurring shear stresses, temperatures and the degree of melting of a film component with the experimentally determined film deformation during overmolding. The degree of deformation thus determined could then be imported back into Moldflow and displayed as a color plot. The process was thus optimized and experimentally validated with regard to the lowest possible damage. The methodology illustrated by this example can also be applied to many other specific problems.
Sebastian Schwan, Institut für Kunststoffverarbeitung Aachen
Compensation of part warpage in injection moulding using local thermal sprayed ceramic heating layers
Warpage can occur in injection-moulded plastic parts due to local differences in shrinkage. These local differences can be caused, for example, by different cooling rates when the injection-moulded parts cool down. Homogenisation of the local temperatures can therefore be sought to reduce warpage. As part of a DFG-project, ceramic heating layers are being developed which can locally influence the mould wall temperature and thus the material temperature in order to produce a homogeneous temperature distribution and, as a result, less warpage. For this purpose, ceramic heating layers are applied by thermal spraying to areas that cool down slowly, such as the inside of corners. Due to their low thickness, the layers can be heated dynamically and adapted to the temperature of the inside of the corner. This ensures uniform cooling across the wall thickness, which reduces the formation of internal stresses in the moulded part and thus the occurrence of warpage.
Blazej Paluszynski, BASF, Material Research
Influence of material data quality on shrinkage and warpage results
The quality of simulation results depends on three essential factors: realistic physical models, correct modeling (boundary conditions and discretization of the part), and accurate material data.
In this presentation, we discuss the quality of material data and its effects on shrinkage and warpage results. We present findings of a sensitivity study on various material data, such as pvT and thermal expansion coefficient, which have an impact on shrinkage and warpage. Based on these results, we analyze the quality of available material data in Moldflow. Finally, we provide practical tips to users on how to check the reliability of material data.
Thomas Willerer, Webasto SE, Development Expert
Improving Simulation Accuracy in Injection Molding: A History of Investigating Moldflow Rotational Diffusion (MRD) Fiber Orientation Model Parameters Using a Design of Experiments (DOE) Approach
Dr. Martin Hohberg, Simutence GmbH, Composites Simulation Specialist
LFT tape underbodies for electromobility: thermal simulation using SimuTerm as the basis for a robust compression molding simulation
Electromobility requires new lightweight construction strategies due to the additional weight of the batteries. These solutions must be able to withstand both thermal boundary conditions, e.g. the thermal runaway of the battery, and mechanical boundary conditions, e.g. impact. One of these solutions are LFT tape sandwiches, such as those used in series production in the Q6 e-tron (see Figure 1).
With their dimensions of between 1 and 3 m² and the many process steps involved, such components pose major challenges for process simulation. First, the tape is heated, then the extruded LFT plastic certificate is placed on the lower tape and covered with the second tape. This is followed by a transfer into the tool before the extrusion process begins. The temperature distribution in the tape and LFT at the start of pressing is decisive for the filling of the component and its component quality. For this reason, Simutence has developed a virtual process chain that uses the thermal simulation tool SimuTherm as a central tool to determine the initial temperature depending on the handling and to initialize it in Moldflow. This virtual process chain will be demonstrated and validated in this presentation on a tape LFT sandwich underbody, which was developed together with AUDI, ElringKlinger and the Fraunhofer ICT and IGCV as part of the publicly funded protECOlight project.
Michael Käfer, Melecs EWS GmbH, Senior Mechanical Design Engineer
Warpage prediction put to the test. Comparison of simulations vs. moulded parts using an experimental injection-moulding tool.
For electronic housings, demanding dimensional tolerances lead to long tool correction loops. To improve part quality and reduce tool correction efforts an accurate warpage prediction is key. An experimental injection-moulding tool was built for the purpose of producing housings with different injection-locations and housing geometries.
In this presentation, we take a look at housings produced from PA66 GF30% with different feed and geometry options. In a comparison between simulated warpage and measured warpage on moulded parts, we will put Moldflow to the test: How accurate is the warpage prediction?
Finally, we provide insights into what we have learned from this journey and how we improved our development process for electronic housings.
Prof. Dr. Gianluca Trotta, STIIMA, Assistant Professor
Sensitivity analysis of the rheological model main parameters to evaluate improvements of micro injection molding simulations accuracy
The identification of an appropriate rheological model for polymer materials, facilitating accurate predictions of the micro injection molding process, constitutes a subject of current significance and substantial scientific interest. This is particularly the case when high accuracy and miniaturized features are required, for example in scenarios involving micrometric geometries such as those encountered in microfluidic devices for biomedical applications. In this context, the current study investigated the rheological behavior of thermoplastic materials during the micro injection molding process. Specifically, the deviations between simulated predictions compared to real experimentation carried out on the DesmaTec FormicaPlast 1K micro injection molding machine were analyzed. A sensitivity analysis of the main viscosity model parameters was carried out to provide clear insights into potential interventions targeting parameters of the reference rheological model acknowledged as exerting the most significant impact on viscosity. The comparisons between simulated filling analyses and those resulting from experiments were based on the response variables obtained from an instrumented two-cavity micro tool which used two sensors capable of providing melt pressure and temperature at the corresponding sensors positions, the pressure and temperature variation between the two sensors, as well as the time needed by the melt to flow between the two sensors.