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Active research projects in the field of simulation

Connect4HCA | 2024-2028

Connectivity for Human-Centered Automation 5.0

Implementation of advanced connectivity technologies and structures in production

By taking a holistic view of connectivity, the Connect4HCA project places people at the centre of industrial automation. The concept of connectivity ranges from the integration of processes, plants, production lines and locations as well as supply chains to systems and data across their lifecycles. Furthermore, the term connectivity encompasses both the interaction from technology to technology and between human and artificial intelligence. In the future, decentralised technical intelligence will shape the entire value chain along the product life cycle together with humans. To this end, a holistic demonstrator is being created as a research platform, in which connectivity is considered in several dimensions.

The project is funded by the Federal Ministry for Economic Affairs and Climate Protection on the basis of a decision by the German Bundestag.

 

Project partner

Balluff GmbHDITF - Deutsche Institute für Textil- und Faserforschung Denkendorf
NAiSE GmbHFraunhofer
Siemens AGNokia
Arena 2036 e.V.       Institut für Steuerungstechnik der Werkzeugmaschinen und Fertigungseinrichtungen (ISW) Universität Stuttgart

SkaLab | 2023-2025

A scalable centre for the flexible production of customisable sheet metal components

The SkaLab project is creating a scalable bending cell. The aim is to develop and test highly flexible, mass-produced manufacturing centres for sheet metal car body components that are scalable in all dimensions (geometry, semi-finished product, material, production quantity). The manufacturing centres should make it possible for the first time to change the process sequence in series production to suit individual components. This should reduce the manufacturing costs for new, geometrically different body variants.

The project is funded by the German Federal Ministry of Education and Research on the basis of a decision by the German Bundestag and by the European Union.

 

Project partners

HMT AutomotiveFranz Hof HmbH 
MPA Technology​ Fernuniversität Hagen
Universität SiegenTWT
VIA Consult​ voestalpine

TwinMaP | 2023-2025

Digital twin of a heterogeneous machine park for the complete machining of components

In the TwinMaP project, digital twins are created at various levels (e.g. simulation models for the VIBN) to optimise the production of small and medium batch sizes. A special feature is the heterogeneous machine park consisting of existing machines and new machines. 

The project is funded by the Federal Ministry of Economics and Climate Protection.

Project partners

ISG Industrielle Steuerungstechnik GmbH​ Trumpf Gruppe 
Daimler Truck – EvoBus GmbH​ VELIT Consulting GmbH & Co. KG
SimPlan AG​ ifak e.V.​ 
FORCAM GmbH​ IPI – Institut für Produktion und Informatik​, Technologietransferzentrum (TTZ) Sonthofen im Allgäu

 

FastPeM | 2023-2027

Reducing the production costs of fuel cells

The focus of the FastPeM: Accelerated testing process for mass production of fuel cell stacks project is on the testing processes downstream of fuel cell stack production and their optimisation.

The project is funded by the Baden-Württemberg Ministry of Economic Affairs, Labour and Tourism. Co-financed by the European Union. Part of RegioWIN.

 

Project partners

Campus SchwarzwaldMarquardt Management SE
teamtechnik Maschinen und Anlagen GmbHSchnorr GmbH
Fraunhofer IPA 

ViPro | 2022-2025

Virtual planning, design and commissioning of complex, robot-based processes for handling compliant objects

In many areas, the efficiency and quality of control software is already increasing through the use of virtual commissioning. Until now, however, virtual commissioning has failed to simulate flexible objects, such as those in the food, pharmaceutical and packaging industries. The aim of the project is to develop new simulation methods that map the essential static and dynamic phenomena of handling compliant objects and enable simple modelling of these handling processes. This means that the advantages of a VIBN can also be utilised in handling applications for flexible objects.

The project is funded by the Federal Ministry of Education and Research on the basis of a decision by the German Bundestag.

 

Project partners

PREMIUM ROBOTICS GmbHInstitut für Systemdynamik (ISYS), Universität Stuttgart

SDM4FZI | 2021-2024

Software-defined manufacturing for the automotive and supplier industry

In the large-scale project SDM4FZI, the topic of changeability in production is being addressed with 30 project partners. The focus is on the efficient creation of software with the help of model-driven approaches and the use of digital twins in order to be able to carry out software tests across the entire life cycle and all levels of a production plant.

The project is funded by the Federal Ministry for Economic Affairs and Climate Protection on the basis of a decision by the German Bundestag.

 

Project partners

Robert Bosch GmbHBosch Automotive Steering GmbHBosch Manufacturing Solutions GmbHBosch Rexroth AG
AUDI AGAudi Planung GmbHEPLAN GmbH & Co. KGTRUMPF Werkzeugmaschinen GmbH+Co.KG
HOMAG GmbHPilz GmbH & Co. KGABB AG - Forschungszentrum DeutschlandABB Automation Products GmbH
ABB Automation GmbHBalluff GmbHCarl zeiss Industrielle Messtechnik GmbHNAGEL Maschinen- und Werkzeugfabrik GmbH
HEITEC AGCODESYS Development GmbHISG Industrielle Steuerungstechnik GmbHSCALE it eG (i.G.)
ASCon Systems GmbHSimPlan AGSOTEC Software Entwicklungs GmbH+Co. Mikrocomputertechnik KGEXAPT Systemtechnik GmbH
KENBUN IT AGIngenieurbüro Roth GmbH & Co. KG23 Technologies GmbHflexis AG
Universität StuttgartKarlsruher Institut für Technologie  

KausalAssist | 2021-2024

Causal graphs as a learning assistance system for automated error management in production

With the ever-increasing networking and software upgrades in production, additional highly qualified specialists are currently needed in fault management.

The KausaLAssist project aims to use AI-based causal graphs to learn error cases on the digital twin of the real plant. With the help of the trained causal relationships, the plant personnel can be supported in troubleshooting during operation and thus contribute to efficient fault management.

The project is funded by the Federal Ministry of Education and Research on the basis of a decision by the German Bundestag.

 

Project partners

Fraunhofer Institute for Machine Tools and Forming Technology IWUInstitut für Angewandte Informatik e.V.Schuster Maschinenbau GmbHKAMAX Tools & Equipment GmbH & Co. KG
Industry-Partner GmbH CoswigSEITEC GmbHqueo GmbH 

AICoM | 2021 - 2024

Learning machine tool for autonomous milling of customised workpieces

The aim is to develop a learning machine tool for metal-cutting production with the ability to adapt the process autonomously and to draw on learnt "knowledge" or learnt "experience" in order to be able to use the high level of process understanding required cost-effectively, even for small quantities.

The information required for this is fed back to AICoM through processed internal machine or external sensor data as well as through a scalable and real-time-capable process model.

The project is funded by the Federal Ministry of Education and Research on the basis of a decision by the German Bundestag.

 

Project partners

Technische Universität Darmstadt - Data Management

Technische Universität Darmstadt - Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen

Gühring KG

Datron AG

ModuleWorks GmbH

Synop-Systems UG

Lorenz Hoffmann

 

 

KI-Steuerung | 2021-2025

Research into automated control programming using machine learning

Digital twins are already being used today for virtual commissioning in order to be able to test control software independently of the hardware structure of the real system.

The aim of AI control is to use the digital twin as early as the control programming stage and to automate this using machine learning. This massively shortens the software development process, which offers an essential market advantage as the number of product variants increases and time-to-market decreases.

The project is funded by the Federal Ministry of Education and Research on the basis of a decision by the German Bundestag.

 

Project partners

Institut für Steuerungstechnik der Werkzeugmaschinen und Fertigungseinrichtungen (ISW) Universität Stuttgart

IT Engineering Software Innovations GmbH