Artificial Intelligence for Humans and Machines

Research

We research on new, practice-oriented solutions for better value creation. And we support you in the application process.

Projects

We identify potential and advise on implementation. In research projects. You and us. Together with others.

Transfer

Transferring knowledge into practice and unlocking potential is our specialty. By applying new smart technologies in products, production, and logistics.

Training

We train your employees in new technologies and their usage. With a practical and implementation-oriented approach.

Technology

We know technologies and use them. AI, Industry 4.0, Cobots. 5G, blockchain, and IT systems.

Solutions

We use technologies. For your new products, services, or solutions in the value added process.

Project AI4DT

Artificial Intelligence for Digital Twins (AI4DT) is a project to establish a joint research network linking the Dutch region of North Brabant and Baden-Württemberg. The initiative focuses on cross-border networking between companies and research institutions, supporting small and medium-sized enterprises in opening up markets, and transferring solutions and knowledge in the areas of smart industries, digital twins, artificial intelligence, and Industry 4.0 into practical applications.In addition to the Ministry of Economic Affairs, Labor and Housing of the State of Baden-Württemberg and the Dutch province of North Brabant, the Consulate General of the Kingdom of the Netherlands is also supporting the establishment and operation of the AI4DT network. The Reutlingen Center for Industry 4.0 at Reutlingen University, the Fraunhofer Institute for Manufacturing Engineering and Automation, IPA, and the Steinbeis Innovation Center are also participating in the network. Regional networks such as the Dutch Smart Industry NL and Brainport Industries, as well as the Industry 4.0 Baden-Württemberg Alliance and advisory centers such as the Steinbeis Europe Center, are also involved.

In addition to the Ministry of Economic Affairs, Labor and Housing of the State of Baden-Württemberg and the Dutch province of North Brabant, the Consulate General of the Kingdom of the Netherlands also supports the establishment and operation of the AI4DT network. The Reutlinger Zentrum Industrie 4.0 at Hochschule Reutlingen, the Fraunhofer-Institut für Produktionstechnik und Automatisierung, IPA and the Steinbeis-Innovationszentrum are also participating in the network. Regional networks such as the Dutch Smart Industry NL and Brainport Industries as well as Allianz Industrie 4.0 Baden-Württemberg and advisory centers such as the Steinbeis Europa Zentrum.

Project TPBW I4.0

The Baden-Württemberg Industry 4.0 Transfer Platform (TPBW I4.0) was founded in 2017 by the universities of Aalen, Esslingen, and Reutlingen in cooperation with the Steinbeis Foundation and with financial support from the Baden-Württemberg Ministry of Economic Affairs, Labor, and Housing.

This transfer platform helps small and medium-sized enterprises (SMEs) in Baden-Württemberg in particular to make better use of opportunities in the field of digital networking and intelligent production. Goals already achieved include efficiency gains in development and production, increased profits, faster development, and safer work processes.

In recent years, the focus has been on the application of artificial intelligence (AI) to further develop the products of medium-sized companies and the use of AI in production and logistics to increase productivity.

https://www.tpbw-i40.de/

Project FILPCO2

The research project is dedicated to the flexible integration of logistics and production using a shared digital model based on the example of the “CO2 backpack.” The aim is to determine common requirements for data management within the entire supply chain. The focus was on calculating, evaluating, and forecasting the carbon footprint of products and developing appropriate countermeasures.

The resulting research demonstrator shows the possible applications of the digital twin. The administration shell plays a central role in various supply chain stages, including CO2 forecasting and the initiation of measures. Requirements for data management, real-time capability, and interfaces were also defined. Close cooperation with industry partners ensured practice-oriented development.

The project was carried out by the Institute for Industrial Manufacturing and Management at the University of Stuttgart and the Steinbeis Innovation Center under the leadership of Campus Schwarzwald. The project was supported by three companies from Baden-Württemberg: Weinmann Aach AG, Arburg GmbH + Co KG, and fischerwerke GmbH & Co. KG, as well as Allianz Industrie 4.0 BW. FILPCO2 was funded by the Baden-Württemberg Ministry of Economic Affairs, Labor and Tourism.

To the press release (in German only)

Projekt IDGreen

The project aims to investigate and test the applicability of blockchain
technology as a basis for cross-company identification systems
in the context of the European Digital Product Passport (DPP).

The focus is on investigating a unique and consistent identification of products and parts throughout their entire life cycle, especially in complex and dynamic value chains such as
mechanical engineering.
The challenges of such identification systems in fragmented value chains are to be overcome by integrating blockchain as the backbone for generating and managing unique identities and
metadata. The secure linking of digital identities and physical products plays a central role in this.

You can find more about the IDGreen Project here

The project is carried on behalf of the Baden-Württemberg Stiftung (Infoflyer English).

Further project examples:

• Monitoring of intralogistics processes and implementation of appropriate measures in the event of defined deviations, self-controlling logistics processes

• Semi-autonomous design and evaluation (economic efficiency and work system value) of production systems using digital twins

• AI-supported method for collaborative semi-autonomous group work between humans and robots

• Optical recognition and automatic classification using a trained artificial neural network in logistics

• AI-based ergonomics analysis and training in assembly and order picking

• Organization and cooperation between individual intelligent systems and their traceability in the blockchain

• Process automation through smart contracts

• Digital product memory and traceability of work creation chains

• Process optimization with the help of pattern recognition