For the Institute of Plastics Processing (IKV) at the RWTH Aachen University, Germany, 2020 is an anniversary year in three different ways. The RWTH Aachen University is celebrating its 150th anniversary, and is marking the occasion, by hosting the International Colloquium of Plastics Technology for the 30th time – with special feature on the previous day. A preview of the celebrations.

Institute Director Professor Christian Hopmann expects 800 participants to attend the 30th International Colloquium of Plastics Technology

A Varied Menu

Extrusion

Kunststoffverarbeitung: Verfahren

Spritzgießen

Doriat, Clemens, Dr.

Temperiertechnik

Künstliche Intelligenz für die Qualitätssicherung

Industrie 4.0

Industrie 4.0 für die Qualitätssicherung

Extrusionswerkzeuge

Kunststoffverarbeitung: Maschinen und Komponenten

Werkzeuge für die Kunststoffverarbeitung

Additive Fertigung

Extrusionsanlagen

Reason to Celebrate 30th International Colloquium of Plastics Technology and  70 Years of the IKV

Maintaining competitiveness while producing in Germany requires not only cost-efficient production, but also high-quality products. Vorwerk Elektrowerke is accepting this challenge. In collaboration with the Institute of Product Engineering at the University of Duisburg-Essen, Germany, the company is testing a 100 % inline quality monitoring system as well as a quality prediction using machine learning.

Customers who choose the Kobold VK 200 vacuum cleaner expect top quality. To ensure this, efforts for the introduction of Industry 4.0 measures are taken in the production plant in Wuppertal, Germany

16:9

Successfully Managing Digital Transformation with Automation and Artificial Intelligence

Mehrkomponenten-Spritzgießen

Digitale Transformation

Wirtschaft

Innovationen und neue Technologie

Kameras, intelligente

Fertigungsautomation

Bildverarbeitung

Industrie 4.0 für die Kunststoffverarbeitung

Machine Learning / Künstliche Intelligenz für die spanende Fertigung

Industrie 4.0 für die spanende Fertigung

Datenanalyse

Inline- / Online-Messsysteme

Qualitätssicherung

Qualitätssicherung Kunststoff

Inline Quality Monitoring and  Data-Based Quality Prediction

The Circular Economy is not only the theme topic at the K 2019. It is also the “green” thread running through the fair exhibit by Engel, the provider of injection molding machines and integrated system solutions. Industry 4.0 is turning out to be a driving force for recycling. This is a most timely insight, since the branch is in for several economically cool years.

Dr. Stefan Engleder, CEO of the Engel Group: “The plastics industry bears a  global responsibility.”

Engel Supports Strong Involvement by the Plastics Industry in a Circular Economy

Folientechnik (IMD, IML, FIM, u.a.)

Verbundwerkstoffe / Werkstoffverbunde

Kunststoff Werkstoffe

Spritzgießmaschinen

Co-Injektion (Barriere-/Sandwich-Spritzgießen)

Kunststoff-Recycling

Kunststoff-Aufbereitung

Organobleche (gewebeverstärkte Thermoplast-Halbzeuge)

Halbzeuge und Zwischenprodukte

Kunststoff-Halbzeuge

Ressourcenmanagement

Produktion

A Second Life for Plastics

Lightweight parts, energy-saving processing or the practice of combining several process steps into one can all be subsumed under one current buzzword: sustainability. A technology that is highly promising in this regard is thermoplastic foam injection molding.

In physical foam injection molding, a blowing gas is injected into the polymer melt during plasticizing

New Developments in Thermoplastic Foam Injection Molding

Schaumspritzgießen

Schnecken und Plastifiziersysteme

A Special Process that Is Becoming a Sustainable Normal Case

According to researchers of the University of Sydney recycling robots could help solve soft plastic waste crisis.

Abfallverwertung

Energieeffizienz

Prozess- und Umwelttechnik

Technik Trend

kunststoffe-international.com

Kreislaufwirtschaft

Artificial Intelligence against Soft Plastic Waste

Over past months, many in-house workflows and development processes have slowed down and also changed. Nevertheless, time has not stood still, also not in injection molding technology. The debate and development have been shaped by two themes: digitalization and the circular economy. Below are some examples of developments and projects that underpin this trend.

Two displays are seamlessly integrated into the continuously 3D-formed instrument panel

Innovative Injection Molding in Times of Pandemic

Steuern, Regeln

Software

Spritzgießwerkzeuge

Biokunststoffe

Spritzgieß-Sonderverfahren

Nachhaltigkeit

Umweltmanagement

Spritzgießsimulation

Simulation

Lasermarkieren

Oberflächentechnik

Laserbearbeitungen

There Is More beyond the Horizon

The latest trend in digitization  is the Artificial Intelligence of Things. It amounts to “marrying” Artificial Intelligence with the Internet of Things. In the following interview, Martin Dimmler and Martin Rugfelt discuss how companies can profit from AIoT and what plastics manufacturers can learn from its pioneers in other industries.

Where Artificial Intelligence of Things (AIoT) is used, value-adding opportunities for more efficiency, quality, and thus higher sales can be realized in every industry

Artificial Intelligence of Things: Trends and Models for the Plastics Industry

Vernetzung / Cloudlösung für die Kunststoffverarbeitung

IoT-Plattformen für die Qualitätssicherung

Fernwartung / Ferndiagnose

Instandhaltung

Produkt- / anbieterspezifische Automatisierung

Automatisierungstechnik

Automatisierungszellen

IoT-Plattformen für die Kunststoffverarbeitung

“Intelligent Automation Brings Systems Closer to their Optimum”

Cost risks and the loss of knowledge threatened by demographic change, form a scenario for the toolmaking industry for which automated tool design could be a conceivable way out.

Partial automation of the demolding system represents an important step towards complete automation of injection mold design.

Automated Design of the Demolding Systems of Injection Molds

Werkzeugkonstruktion

Dienstleistungen

Werkzeug-, Formen- und Modellbau

Machine Learning

Analysetools, FEM

Machine Learning für die Qualitätssicherung

Digitaler Zwilling

Anticipation of a Larger  System Landscape

Optically excited Lockin-Thermography is well suited for fast and robust detection of near-surface defects in isotropic and fiber-reinforced plastics. The resulting phase images are driven by the excitation frequency as a measurement parameter and can be analyzed in the one-dimensional case for depth-selective evaluation. For real test specimens, however, diffusive heat conduction processes overwhelm which makes accurate defect characterization from phase images much more difficult. Neural networks are used within this work to evaluate multiple phase values of different excitation frequencies with each other and thus implement for the first time a quantitative defect characterization in isotropic and fiber-reinforced plastics based on a LSTM-CNN hybrid model. It is shown that the already good prediction values of the neural network are again significantly improved by additional training data obtained from heat flow simulations.

Representation of the experimental setup: thermographic camera (bottom left), photodiode (top left), VCSEL array (right), CFRP test specimen (center).

Andere Werkstoffe

Faserverbundwerkstoffe

Polymethylmethacrylat

Thermoplaste

Defect characterization in isotropic and fiber-reinforced plastics using active thermography and neural networks

Arburg GmbH + Co. KG, Loßburg, Germany, is new on the market with its Freeformer 300-3X. The large machine will process three components using the Arburg Plastic Freeforming (APF) process, enabling the industrial additive manufacturing of complex functional parts in resilient hard/soft combinations with support structure as a world first. 

More Applications for Arburg Plastic Freeforming 

Resilient Functional Parts in Hard-Soft Combination 

Audi expects significant reduction in prototyping lead times for tail light covers by using a full color 3D printer. Compared to traditional methods, the turnaround times should be halved. The Stratasys J750 makes it possible to produce transparent, multi-colored parts meeting texture and color-matching requirements of Audis stringent design approval process . 

Audi Shortens Release Cycles with Full-Color Multi-Material 3D Printing 

Design in the Fast Lane 

As part of a collaborative initiative, the Brightlands Chemelot Campus focuses on the development and implementation of advanced additive manufacturing technologies. Three current biomedical projects illustrate the multiple possibilities for start-up companies in this market. 

Medical Device Developments at the Brightlands Chemelot Campus 

Polyamide

Medizintechnik

Breeding Ground for Additive Manufacturing 

Arburg Plastic Freeforming (APF) is based on qualified original materials in the form of plastic granulates as used in injection molding. Current researches illuminate influences on the resulting part quality of this additive process. Because the open system permits adaptation of the parameters, the mechanical and geometric properties of the parts can be optimized in a targeted manner. In this way, tensile strengths and part densities comparable to those of injection molded parts can be achieved. 

Arburg Plastic Freeforming: Current Investigations on Part Optimization 

Rapid Manufacturing

Werkstoffprüfung, mechanisch

Droplets to the Beat of Milliseconds 

A new joint venture is getting a hybrid manufacturing cell ready for market. A screw-based plasticizing unit is mounted on a 6-axis robot. The novel processing approach facilitates additive manufacturing of structural parts from granular and fiber-reinforced standard compounds.   

High-Speed Additive Manufacturing of Fiber-Reinforced Structural Parts 

Compound

Kohlenstofffasern / -matten

Flexible Fertigungssysteme

Layer-by-Layer from Granulate to Part 

ElogioAM B.V., a newly formed Joint Venture between Swedish Perstorp AB and Dutch 3D4Makers B.V, introduces new filament solutions. Facilan HT is specifically designed for 3D printing. It is a safe copolyester with high temperature resistance with heat deflection temperature of 89°C. Its high stiffness enables design optimization for faster rigid part print jobs. 

Joint Venture Introduces New Filament Solutions 

Durable Parts with Facilan HT 

German Scientists want to develop an app for automatic monitoring of print quality in additive manufacturing at batch size 1.

Scientists from Hanover and Aachen are working on a solution to support small and medium-sized companies in particular in the approval of patient-specific medical devices from the 3D printer

3D printing enables a batch size 1 production, meaning no products are alike because each part is individually designed for the customer. Among others, this is interesting for the medical technology sector. Additively manufactured dental splints, hearing aids and even implants can be perfectly adapted to the body of an individual patient and still be produced cost-effectively. One challenge for companies, however, is quality assurance. Personalized medical devices are subject to strict safety requirements. Manufacturers must be able to guarantee that there are no invisible cracks or pores in the component and that the geometric requirements and desired material properties are achieved. Scientists from Hanover and Aachen are working on a solution to support small and medium-sized companies in particular in the approval of patient-specific medical devices from the 3D printer: they want to develop an app that helps with quality assurance.

The more individualized the production, the more difficult quality assurance becomes. In the case of goods manufactured in large series, it is often sufficient to carry out quality tests on a few randomly selected products in order to be able to draw conclusions about the entire batch. This is not possible with single-item products. Here, each component must be examined in detail to ensure quality.

Detecting possible defects in patient-specific 3D printed products during production is the goal of a new research project being conducted jointly by scientists at the Institut für Integrierte Produktion Hannover (IPH) gGmbH and the Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University.

Artificial Intelligence to Detect Production Errors

The researchers want to equip an industrial 3D printer with sensor technology to seamlessly monitor the printing process. The sensor data will be evaluated in an app using Artificial Intelligence via a quality model to reliably detect production errors. The scientists at the IPH and the WZL are focusing primarily on medical technology, because in this industry the degree of individualization of products and the associated quality requirements are particularly high, and proof of a quality assurance system must be provided as part of an approval process. In the research project, the IPH is responsible for sensor technology and data collection, while the WZL is responsible for creating the quality model and programming the app.

Quality in 3D printing is influenced by many factors: the type of material used, the ambient temperature, the temperature at which the filament is melted, the printing speed, the vibrations of the print head and quite a few other parameters. “Additive Manufacturing processes are very sensitive to external influences,” says project engineer Anne Rathje from IPH. “Our goal is to get more safety into the process and avoid errors.” Particularly treacherous, she says, is that many errors are no longer visible from the outside once the component has finished printing. “For example, if the print head clogs briefly in between and then continues to print normally, you won’t see it later,” Rathje says.

For the research project, IPH is using the X500PRO industrial printer from German RepRap GmbH. The printing material used is the plastic acrylonitrile butadiene styrene (ABS), which has a comparatively high strength but is very sensitive to temperature.

The scientists want to use various sensors to monitor the print quality. Conceivable options include sensors that measure the temperature of the build plate or build chamber, infrared sensors that can be used to determine the temperature directly at the print head, vibration sensors and optical measurement technology. Acoustic signals – in simple terms, sound recordings – are also useful for quality monitoring. These could be used, for example, to determine if the print head is clogged or if the filament breaks in the system. “You can hear that,” says Anne Rathje. “The challenge, however, is to process the signals in such a way that ambient noise is filtered out” – for example, the whirring of the motor in the 3D printer, the noise of the computer or a slammed door. To distinguish important from unimportant sounds, the researchers want to use Machine Learning, a form of Artificial Intelligence. By training the program with as many sound recordings as possible, it learns better and better how to reliably detect errors based on acoustic signals.

The App Provides Data – the Users Have to Interpret It

Ultimately, the goal is to develop an app that automatically evaluates all sensor data. “Our goal is to reduce the effort involved in quality assurance in 3D printing and also to enable laypersons to monitor the print via an intuitive app,” says Anna-Lena Knott from the WZL. Users do not have to interpret the sensor data – the app monitors the entire printing process, documents errors and provides feedback on print quality. In the event of serious errors that could render the component unusable, the app stops the printing process and informs the user. The print settings can then be adjusted and specialist personnel called in if necessary.

The IPH and the WZL are working closely with industry on the research project. The project advisory committee includes manufacturing companies from medical and dental technology and other industries, as well as manufacturers of 3D printers.

The IPH and WZL are working closely with industry on the research project. The project advisory committee includes manufacturing companies from medical and dental technology and other industries, as well as manufacturers of 3D printers. The research project, entitled “Sensor- and app-based validation of process and product quality for effort-reduced certification of personalized medical devices (SAViour),” will run until January 2023 and is funded by the German Federal Ministry for Economic Affairs and Energy.

Werkzeugmaschinenlabor WZL der RWTH Aachen University 

https://www.wzl.rwth-aachen.de

IPH - Institut für Integrierte Produktion Hannover gemeinnützige GmbH 

https://www.iph-hannover.de

Quality monitoring: the scientists will attach sensors to the printer to detect faults such as a clogged print head

3D printed dental splints: thanks to additive manufacturing, medical products can be individually adapted to the patient’s body and still be produced cost-effectively

3D printers in the dental lab: Rainer Ulbricht Dental-Technik GmbH already uses additive manufacturing and participates in the SAViour research project

Professional 3D printing system: in the research project, IPH uses the X500PRO industrial printer from German RepRap GmbH and equips it with sensor technology