70th CIRP General Assembly 2021

Virtual Coffee Break - Room 'Fraunhofer'

 

26.08.2021 

12:30 - 13:00

27.08.2021

14:30 - 15:00

Additive + x - Hybrid Additive Manufacturing and Post Processing

Prof. Dr.-Ing. Christian Seidel, Fraunhofer IGCV

Prof. Dr.-Ing. Michael Schmidt, Friedrich-Alexander-Universität

 

Fraunhofer Research Fab Battery Cells

Prof. Dr.-Ing. E.h. Dr.h.c. Fritz Klocke, Fraunhofer IPT

 

 

 

 

 

 

 

Issuing Institutes

Energy-oriented Production Planning and Control: Scheduling

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In order to achieve the goals of the international climate agreement, the German government has decided to phase out coal and nuclear power generation. At the same time, the share of electricity generation from wind and solar energy must be increased in order to achieve greenhouse gas neutrality of the electricity generated and consumed in Germany by 2050. Since electricity generation from renewable energy sources such as wind and solar energy can only be adjusted to current energy demand to a limited extent, the associated fluctuating electricity generation poses major challenges for the electricity grids and a significant increase in electricity price volatility can be expected. One possible solution to address these challenges is the expansion of industrial demand side management (DSM), also known as energy flexibility (EF). In this context, the Energy Flexible Factory is an opportunity for the grid, but also offers an economic opportunity for companies by shifting consumption to low price windows.

PROPERTY-CONTROLLED METAL FORMING PROCESSES

This research project aims to develop a property control system for the skin-pass rolling process based on roughness-measurements of the outgoing strip topography. The surface topography im-printed during skin-pass rolling significantly influences important properties of metallic semi-finished products such as paintability or tribological properties. Today, the skin-pass rolling processis controlled by specifying a rolling force. The latter is calculated in advance using models which describe the surface imprinting of the textured roll. For this purpose, a fast meta-model based on a complex multiscale simulation was derived to describe the roll’s imprinting. Additionally, a correc-tion model identifying the roll wear is calculated at runtime.

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Artificial Intelligence

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Drilling application for machining of large ship propellers

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High precision machining of ship propellers

The MMG company in Waren (Müritz) is one of the world‘s leading manufacturers of ship propellers. The ship propellers with a diameter of up to 12 metres are cast from copper-aluminium alloy. The manufactured blanks are ground to the nominal dimension after casting. As a reference dimension for the grinding process, up to 1.000 marking holes are drilled in a defined grid on all blades surfaces. Until now, the holes were drilled in a very time-consuming manner using a manually operated drilling machine. Together with MMG, the engineers of Fraunho-fer IGP have developed a drilling robot application to drill the target points automatically.

Handling system for automated cold plastic formings

Fraunhofer IGP is working with Ostseestaal and the University of Rostock in a project to develop a handling system for automated cold plastic forming.

Three-dimensional forming of heavy plates for shipbuilding, fascia construction, mould construction and the field of rene-wable energies all depend on a multi-stage cold plastic forming process which facilitates free bending. A crane system hand-les the positioning of heavy plates. Control of the process is contingent on the experience and purely subjective assessment of the plant operator. To increase the efficiency of the process and to archive the experience of plant operators, scientists at Fraunhofer IGP, the University of Rostock and the employees of Ostseestaal are working on automating this handling system.

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Smart Maintenance – From Isolated Applications to Holistic concepts

Fraunhofer IPK Smart Maintenance Testbed / Intelligent real time condition monitoring and failure forecasts using inexpensive sensors and machine learning

Modern industrial production is precision work in more than one respect. Products are manufactured to exacting standards, requiring machine tools’ mechanics to operate reliably and with uncompromising accuracy – unwanted vibrations for example can cause flaws in the required product geometry and lead to expensive waste. Similarly, manufacturing processes usually follow a tight schedule. disruptions or machine breakdowns mean lost time and, potentially, incur contractual penalties when delivery deadlines are missed.

Smart and predictive maintenance is meant to recognize any signs of damage or wear and tear in machine components at the earliest possible time in order to avoid unplanned and unexpected failures. Sensors fitted to machines keep track of active operations and measure temperature, vibration, energy consumption, and many other parameters. Whenever there are deviations from the norm or signs of potentially problematic trends, the system triggers an alarm so that operators can start countermeasures. However, most commercially available monitoring systems remain isolated proprietary solutions that only track the condition of individual components.

VR Tour at »FFB Workspace«

Datenschutz und Datenverarbeitung

Wir setzen zum Einbinden von Videos den Anbieter YouTube ein. Wie die meisten Websites verwendet YouTube Cookies, um Informationen über die Besucher ihrer Internetseite zu sammeln. Wenn Sie das Video starten, könnte dies Datenverarbeitungsvorgänge auslösen. Darauf haben wir keinen Einfluss. Weitere Informationen über Datenschutz bei YouTube finden Sie in deren Datenschutzerklärung unter: http://www.youtube.com/t/privacy_at_youtube

VR Tour at »FFB Workspace«

ULTRA-FAST 3D PRINTING USING STANDARD GRANULES

3D printing opens up completely new approaches for products and manufacturing. However, many 3D printing processes are expensive and too slow for industrial use, where it is essential to produce a great number of pieces in a short period of time. For this purpose, Fraunhofer IWU developed SEAM, a system and process that is eight times faster compared to conventional 3D printing methods.