Active research projects in the field of simulation

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. Up to now, however, virtual commissioning has failed in the simulation of compliant objects, e.g. from the food, pharmaceutical and packaging industries.

The aim of the project is the development of novel simulation methods, which represent the essential static and dynamic phenomena of a handling of compliant objects and allow a simple modeling of these handling processes. Thus, handling applications of compliant objects can also benefit from the advantages of a virtual commissioning.

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

Project partner

robomotion 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 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 perform software tests over the entire life cycle and all levels of a production plant.

The project is funded by the German Federal Ministry of Economics and Climate Protection based on a resolution of the German Bundestag.

Project partner: 

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

H2FastCell | 2021 - 2023

Demonstrator pilot plant for the production of fuel cell systems

For the economic assembly of the time-consuming and precise process, a 1Hz high-speed assembly is to be designed and built using suitable automation components in order to test the challenges and feasibility of a 1Hz assembly.

The design, conception and optimization of the process and the plant will be carried out on the digital twin.

The project is funded by invest bw based on a resolution of the German Bundestag.

Project partner

Campus Schwarzwald (Centrum für Digitalisierung, Führung und Nachhaltigkeit Schwarzwald GmbH)Fraunhofer-Institut für Produktionstechnik und Automatisierung IPAWeiss GmbH
J. Schmalz GmbHi-mation GmbHteamtechnik Maschinen und Anlagen GmbH

 

KausalAssist | 2021 - 2024

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

With the ever increasing networking and software upgrading of manufacturing, additional highly qualified specialists are currently needed in fault management.

The KausaLAssist project aims to learn AI-based fault cases on the digital twin of the real plant using causal graphs. With the help of the trained causal relationships, 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 based on a resolution of the German Bundestag.

Projektpartner

Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWUInstitut für Angewandte Informatik e.V.Schuster Maschinenbau GmbHKAMAX Tools & Equipment GmbH & Co. KG
Industrie-Partner GmbH CoswigSEITEC GmbHqueo GmbH 

AICoM | 2021 - 2024

Learning machine tool for autonomous milling production of customized workpieces

The goal is the development of a learning machine tool for metal-cutting production with the ability to autonomously adapt the process and to fall back on learned "knowledge" or learned "experience" in order to be able to use the high degree of necessary process understanding cost-effectively even for small quantities.

The information required for this is fed back to AICoM through processed machine-internal 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 based on a resolution of the German Bundestag.

Project partner

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

 

 

Requirement-to-Development Digital Twin R2D2-Twin | 2021 - 2024

Development of a new tool and associated methods for the use of 3D simulation in the requirements phase of machines and plants

Users of the new tool of the R2D2-Twin are machine and plant manufacturers as well as system integrators; the current customers of ISG Industrielle Steuerungstechnik GmbH and users of the VIBN tool ISG-virtuos.

By means of the R2D2-Twin, the communication between customer and machine/plant manufacturer in the requirement phase shall be enabled by the tool-supported creation of the requirement specification and immediate visualization of the current variant in a new scale. This sets itself apart from conventional and time-consuming requirements generation. The tool support by the R2D2-Twin can be understood as an intelligent assistance system, which transports knowledge of the manufacturer, validates requirements extensively, visualizes requirements and provides simulation models for discussion and requirements reflection.

The project is funded by the Central Innovation Program for SMEs based on a resolution of the German Bundestag.

Project partner

Institut für Steuerungstechnik der Werkzeugmaschinen und Fertigungseinrichtungen (ISW)Universität Stuttgart
IMA Schelling Deutschland GmbHZimmer GmbH

KI-Steuerung | 2021 - 2025

Exploring automated control programming using machine learning.

Nowadays, digital twins are already used for virtual commissioning in order to be able to test control software independently of the hardware structure of the real plant.

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

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

Project partner

Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW)Universität Stuttgart

IT Engineering Software Innovations GmbH

 

 

SmartAdditive | 2020 - 2022

Development of a novel coupling of a digital twin for the use of simulation models in real time (process simulation in the loop) as well as a comprehensive, optimized trajectory planning

The aim of the project is to develop a novel, automatic control system for additive manufacturing that takes into account the material behavior in the print head: SmartAdditiv.

By modeling the dynamic material behavior in the print head, the volume flow can be precisely controlled for the first time. Combined with real-time path planning on the CNC control, a uniform output is achieved for the first time, i.e. path speed / extrusion speed = constant.

The project is funded by the German Federal Ministry of Economics and Technology based on a resolution of the German Bundestag.

Project partner

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

Ingenieurbüro ROTH GmbH & Co. KG

 

MRiLS | 2020 - 2023

Hybrid interaction concept for training using mixed-reality-in-the-loop simulation

Well-trained specialists form the basis for Germany's success as a business location. With the increasing complexity and networking of production plant manufacturing, training is thus a central component.

The aim of this project is to use digital twins from the engineering process in training in order to avoid downtimes at the real plant. Additionally, immersive training in hazardous situations or inaccessible plant areas will be enabled through AR/VR methods.

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

Project partner

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

Virtual Automation Lab (VAL), Hochschule Esslingen

Professur für Erwachsenenbildung und Weiterbildung, Otto-Friedrich-Universität Bamberg

Ingenieurbüro Roth GmbH & Co. KG