Guido Frohnhaus has been Managing Director Technology & Engineering at Arburg for a good two years now. The pandemic restrictions meant that he has made very few appearances outside the company so far, but, as he says himself, he spent the time getting to know the in-house processes at all levels and in great detail. In this interview with Kunststoffe, the 52-year-old talks about the course he plans to set and how crucial the high level of in-house manufacturing and programming expertise is for the company’s independence.

16:9

Spritzgießen

Kunststoffverarbeitung: Verfahren

Doriat, Clemens, Dr.

Digitale Transformation

Wirtschaft

Innovationen und neue Technologie

Spritzgießsimulation

Software

Simulation

Industrie 4.0 für die Kunststoffverarbeitung

Industrie 4.0

Spritzgießmaschinen

Kunststoffverarbeitung: Maschinen und Komponenten

Kreislaufwirtschaft

“Gestica Will Be the Fixed Star in the Customer’s Universe”

The digital shadow is the core concept of the Cluster of Excellence “Internet of Production” at RWTH Aachen University. It represents the data trace of an asset to describe its real behavior. In the Plastics Innovation Center 4.0 (PIC 4.0), digital shadows, e.g. the data trace of a sensor, are used to optimize processes taking into account real behavior and to determine simulation quality.

The construction of the PIC 4.0 proceeds and throws its shadow on the Campus Melaten.

Part 7 of the Series: How the Digital Shadow Enlightens Real Processes in the PIC 4.0

Sensorik für Kunststoff-Verarbeitungsmaschinen

Digitaler Zwilling

Out of the Shadow into the Light

Internal pressure loads are typical for fiber-reinforced plastic components. To increase the burst strength of components, the fiber orientation can be modified in a targeted way during injection molding by means of a rotating mold core. A newly developed simulation method allows this modified fiber orientation to be taken into account at the design stage.

Practical implementation of a mold system with rotating core.

Mold System with Rotating Core Improves Mechanical Properties

Werkstoffprüfung, mechanisch

Messtechnik

Werkstoffprüfung

Spritzgießwerkzeuge

Werkzeuge für die Kunststoffverarbeitung

Verbundwerkstoffe / Werkstoffverbunde

Kunststoff Werkstoffe

Faserverbundwerkstoffe

Andere Werkstoffe

Design Methodology for Parts Subject to Internal Pressure

CoreTech System announced the appointments of Dr. David Hsu as its new Chairman, and Dr. Venny Yang as the new CEO. Dr. Rong-Yeu Chang, founder of CoreTech System, announced his resignation and assumed new roles.

Dr David Hsu (left) and Dr Venny Yang (right) have taken over the roles of chairman and CEO, respectively, from Dr Rong-Yeu Chang (centre)

CoreTech System Appointed New Chairman and CEO

Skilful application of the evaluation and analytical options afforded by process simulation, including designing the best temperature-control system and making comparisons with alternative manufacturing processes, smoothes the way to efficient product development and manufacturing. Doing this from the very start of a project enables investments to be weighed and qualified, and technical, economic or environmental concerns to be taken into account, as exemplified here by a part with a high-gloss surface.

3D CAD view of the conformal temperature-control system for injection molding a fascia with a high-gloss surface.

Predicting the Surface Finish of High-Gloss Plastic Parts

Dynamische / variotherme Temperierung

Oberflächentechnik

Lackieren

Chemisches Bearbeiten (Auftragen)

Qualitätssicherung Kunststoff

Qualitätssicherung

High Gloss – Paintless and Painless

Arburg has adopted a clear message for its trade fair appearance at the K 2022 in Düsseldorf: „There is only a Plan A“.

In the arburgGreenworld pavilion of the VDMA Circular Economy Forum, an Allrounder 370 A with recyclate package is manufacturing “Greenline” wall plugs from Fischer.

Messe K-Kunststoffmesse

kunststoffe-international.com

Mehrkomponenten-Spritzgießen

Nachhaltigkeit

Umweltmanagement

Energieeffizienz

Sustainability thanks to Digitalization

The injection molding machine manufacturer Arburg and the simulation software supplier Simcon presented the first filling simulation directly on the injection molding machine three years ago.

The new tool works on any Arburg injection molding machine with Gestica control.

Exclusive Interview with Werner Faulhaber of Arburg and Paul Filz of Simcon

“We Tear down Walls”

In the conception of functionally integrated and injection molding-appropriate designs, SimpaTec supports the company with up-to-date simulation expertise.

Flooded with water: the new generation of e-bike frames is manufactured by the WAIM process.

Holistic Product Development of a Carbon Fiber-Reinforced Bicycle Frame

Kohlenstofffasern / -matten

Verstärkungsstoffe

Analysetools, FEM

Drop by Drop

A simplified 2-D thermoforming analysis tool for automotive interior components quickly shows the tendencies to be expected for stretching of film or sheet. With a few clicks of the mouse in the CAD system, critical regions can be identified at a very early phase of development and potential remedies verified. 

Warmformen / Thermoformen

Thermoforming Analysis: Quick Overview via 2-D Simulation 

Air flowing through the engine compartment accounts for 15% of the aerodynamic drag of a vehicle. An actively controlled louver behind the radiator reduces both fuel consumption and aerodynamic drag. It was only possible to develop this louver system by employing extensive mold filling simulations. 

Part Design: Louvers Reduce Fuel Consumption 

With Integrative Simulation, part three, which has now been further refined once again, it is possible to predict the strength and fracture behavior of highly-stressed plastic parts, such as engine supports or chassis bearings, in a highly accurate manner. This makes it possible to implement applications in plastics that were formerly confined exclusively to metals. 

Integrative Simulation: Metal as the Virtual Benchmark 

By means of a new method of estimation thermal stresses in unreinforced thermoplastic parts on heating and cooling can be calculated simply and in good agreement with measured values. The method requires only the modulus of elasticity and the coefficient of linear thermal expansion from databases and an empirically determined influencing factor as a measure of the effect of temperature and material characteristics. 

Part Design: Estimating Thermal Stresses Using Single-Point Data 

The simulation of shrinkage and warpage requires a wide range of data specific to a particular moulding compound. Ascertaining this data is a laborious experimental process. The material databases are therefore insufficiently stocked with information. Can this problem be solved by the use of appropriate representative compounds? The authors investigate this question by means of two typical parts, each produced with three different moulding compounds, with the simulation programs Cadmould and Moldflow. 

How does Injection Moulding Simulation of Shrinkage and Warpage Respond to Variations in Material Data?: Simulation with Variations in Material Data 

The quality of the forecasts made by simulation molds is improving all the time, with more and more specialist techniques entering the virtual world. Nearly every new release promises to deliver possibilities and features that will make life easier for designers and model makers – Release 11 of Moldex3D is no different in this regard. 

Injection Molding Simulation: The Parts Forecast for Tomorrow 

Timely simulation to check the mold concept for injection molding is a key element in the successful launch of a product. The simulation plays an important role in developing fit-for-purpose molds in a shorter time and at lower cost. 

Mold Design: Virtual Demolding Forces 

Systematic Approach to a Precision Polymer Gear Wheel

Optimizing a Tricky Component Geometry Using Sigmasoft Virtual Molding

MS-Schramberg has a track-record of developing precision polymer parts for the automotive industry. The example of a gear wheel demonstrates how the efficiency of component optimization can be boosted through the use of simulation.

A great deal has already been reported about the use of Virtual Molding software to plan and analyze injection molding processes from start to finish. However, many people are unaware that this tool  can be used to optimize functionality at the design stage. MS-Schramberg, a company specialized in magnets, has a track-record of developing precision polymer parts for the automotive industry. The following practical example of a gear wheel demonstrates how the efficiency of component optimization can be boosted through the use of simulation.

The customer not only specified the geometry of the component by a 3D model but also the polymer to be used, namely a polyphenylene sulfide reinforced with 40 % glass fibers (PPS-GF40). More particularly, the component has a diameter of around 30 mm and weighs about 5 g. In the real world of injection molding production, deformation resulting from material buildup, fiber anisotropy and shrinkage poses a risk to the functionality of this gear wheel. A gear wheel that undergoes just radial deformation can be allowed for or corrected relatively easy in the injection mold. However, one that is deformed both radially and axially, as expected in this example (Fig. 1), is difficult to correct in practice and therefore requires careful advance planning.

The goal of this project was therefore to optimize the component geometry – reducing axial gear wheel deformation – even before the injection mold had been made. This was done with the aid of Sigmasoft Virtual Molding software (supplier: Sigma Engineering GmbH, Aachen, Germany). The model was imported into the software, the corresponding negative cavity was created, filled with the designated polymer through manually defined sprue points under application of selected parameters (filling time, temperature, etc.) and then cooled.

This highly simplified approach proceeds from a constant cavity wall temperature. The complete mold, with its various plates and circuits for heating and cooling, are only considered at a later stage. As a result, the high outlay on modeling and simulation is reduced and hundreds of scenarios can be simulated within very short time.

Axial deformation of the teeth was minimized by designing a full-factorial virtual test plan designed to evaluate the geometric variation possibilities within the legitimate design space:

<ul><li>six ribs on the bottom,</li><li>six ribs on the top,</li><li>clearance at the bearing seat,</li><li>radius at the toothing.</li></ul>

Each of these four geometric changes was defined as an activatable input parameter for the optimization process, giving rise to 24 or 16 possible designs.

First Optimization Loop: What are the Major Influences?

Concrete implementation: in order that the axial deformation of the larger toothing could be determined, measuring points were defined on the toothing and the central running surface (Fig. 2). It was decided that the target criterion representing the optimum solution would be to minimize delta between the axial deformation of the outer and inner reference points as that would yield toothing of good flatness.

It emerged that ribs on the large surface and the radius on the toothing base offer the greatest potential for improvement. This still left plenty of room for optimization, especially regarding rib design, as so many variables are involved. So, a second optimization loop was then performed to determine the best rib design.

Again, the aim here was to minimize the axial deformation of the toothing. In addition, for economy, the volume was designed to be as low as possible. The following were varied:

<ul><li>the number of ribs: between six and twelve, in increments of 1;</li><li>the height of the ribs: between 0.6 and 1.2 mm, in increments of 0.1 mm, and</li><li>the width of the ribs: between 0.8 and 1.2 mm, in increments of 0.1 mm.</li></ul>

These 7 x 7 x 5 or 245 experiments, too, were subject of a fully automated Sigmasoft DoE (Design of Experiments) simulation. This was done by defining the variables and their values in terms of the respective increments. The entire simulation and evaluation were executed by the system overnight.

The outcome of the optimization was an enormous improvement – delta Z dropped by about 90 % from 0.19 to 0.02 (Fig. 3). As expected, the solutions offering the greatest optimization potential were those which had the most ribs (twelve). These results were presented to the customer (Fig. 4). After approval had been given, the geometry was updated and the production mold was ordered.

Drawing on positive experience gained by MS-Schramberg in previous similar projects, all the simulations were executed with three sprues on the top. Here, of course, the positive aspect of more homogeneous fiber distribution and shrinkage had to be weighed against the higher mold costs and the cost of material losses. But, again, the simulation is expected to quickly yield an accurate answer. Fiber distribution is determined by the number of sprues (Fig. 5). In each case, differences in the extent of filling lead to differences in shrinkage and warpage. This allows an accurate prediction to be made for each tooth on the circumference.

The simulated axial deformation on the large gear wheel already lay within the target range when three gates were used, with four and five gates offering marginal improvements. For reasons of symmetry, five sprues would of course have been unsuitable for twelve ribs – in this phase, the simulation was executed without ribs (Fig. 6). The next stage was to weigh the necessary functionality and economy against the desired and feasible degree of precision. In the end, the series was realized with three sprues, and was accompanied by a corresponding reduction in material consumption.

The case presented here is just one, often forgotten, way of using Sigmasoft software in component and process design. This simulation tool is successfully used, for example, in

<ul><li>the inquiry phase to rapidly determine cooling times, pressure requirements or to identify critical hotspots early;</li><li>component optimization, as in the case described above;</li><li>mold design to resolve issues with flow paths, thermal layout and sprue positions;</li><li>studies of the behavior of the molded part (weld lines, flaws, fiber orientation, shrinkage and warpage);</li><li>process simulation – here the entire mold is operated over an arbitrary number of cycles. This grants a way of evaluating process capability and stability under series production conditions as early as the design stage.</li></ul>

The DoE method with autonomous optimization that was used here is available for each of these stages and offers a way of systematically and precisely studying all kinds of problems.

Sometimes, though, the results of filling simulations are just a first step towards a reliable solution. Details relating to anisotropic material structure, fiber orientation or the deformed geometry after cooling, as determined with Sigmasoft, can be transferred to other FEA tools for a rigidity analysis, crash simulation or a service life simulation via the existing Sigmalink interface. This allows to determine the limits of a design with even greater precision in a follow-on analysis.

The possibility of activating and parameterizing individual geometry elements allowed a large number of geometric influences to be studied without a great deal of modeling effort. The two optimization loops led to a 10-fold reduction in axial deformation of the large gear wheel. The influence exerted on efficiency by the number of gates was accurately determined.

The simulations executed with Sigmasoft confirmed and extended the high level of development expertise possessed by MS-Schramberg. The documented simulations made a solid contribution to constructive discussions between customer and supplier. The gear wheel went into series production with the simulated changes in a three-platen mold (Title figure). The optimized quality feature lay within the desired tolerance right from the start.

Although this report merely reveals how to simulate a resilient design with simple tools, Sigmasoft Virtual Molding is then used to design the injection mold and determine the best processing window. Should unexpected problems arise, the tool helps to systematically run through alternative settings, geometry or material changes to quickly arrive at the best solution.

MS-Schramberg GmbH & Co. KG  

https://www.ms-schramberg.de

SIGMA Engineering GmbH  

https://www.sigmasoft.de

Ausgabenartikel

After component optimization, the gear wheel lay within the desired tolerance as soon as it went into series production

Fig. 1. The expected axial and radial deformation calls for careful component design (5:1 scaling) 

Fig. 2. The target criterion of the first optimization loop was a small deviation in the measuring points in the surface

Fig. 3. Plot of delta Z for the 245 variants against the experiment number (number of ribs increasing to the right)

Fig. 4. Deformation of the customer model versus that of the optimized geometry, with 5:1 scaling. The greatest improvement was obtained with the model having the most ribs

Fig. 5. Average fiber distribution for three, four and five sprues. This gives rise to different degrees of shrinkage and warpage

Fig. 6. Visualization of radial and axial deformation per tooth on the large gear wheel with three to five sprues

Name - Hauptartikel

MS-Schramberg GmbH & Co. KG, whose origins lie in magnet manufacturing, is a producer of hard ferrite magnets, rare earth magnets and polymer-bonded magnets, as well as polymer and polymer composite parts and assemblies as system solutions. Across three plants, approx. 550 employees develop and produce custom articles that are used worldwide in various industries, such as automotive, electrical and medical technology. Founded in 1963, the company has its own in-house tooling and mold-making shop as well as a plant and equipment construction department. Sigmasoft has been deployed here with great success since 2019.

<a href="https://www.magnete.de/de.html" target="_blank">ms-schramberg.de</a>

Wojtek Piecha and Mohammed El Yaagoubi work in the Injection Molding/Process Development department at MS-Schramberg GmbH & Co. KG, Schramberg-Sulgen, Germany.

Katharina Aschhoff is Marketing Manager at Sigma Engineering GmbH, Aachen, Germany. <a href="mailto:marketing@sigmasoft.de">marketing@sigmasoft.de</a>