Research and Development
We Are an Industry Partner for Applied R&D Projects
Solutions for the Industry of Tomorrow
Science in Practice
As an industrial partner in research and development, we focus on the digital transformation of industrial processes. Our core expertise lies in developing innovative solutions in the fields of digitalization, industrial process optimization, machine learning (ML), and artificial intelligence (AI). In addition, we contribute to R&D projects involving IIoT infrastructures, edge and cloud technologies, and administration shells (AAS) to actively support companies on their journey toward Industry 4.0.
By participating in publicly funded research projects in collaboration with leading academic institutions and industrial partners, we help ensure the practical applicability of newly developed technologies. Our projects aim to create efficient, real-world solutions for industry. Examples of this innovation include software solutions such as the datAIndustry App and the ModulFinger App, which support data-driven production process optimization – as well as a newly developed OPC server that simplifies the integration and use of machine data.
Get in touch with us to learn more about our research activities and how they can benefit your projects.
Sustainable Technologies for Our Future
Where Innovation Meets Responsibility
Since 2002, SEITEC has been actively involved in industrial research projects. The application of future-relevant key technologies and the industrial transfer of research results play a central role in our own innovation processes.
Our research activities focus not only on technical excellence but also on generating societal and environmental value. Through our work, we help increase the efficiency of industrial systems while reducing energy and resource consumption. In this way, we combine innovation with responsibility and actively contribute to building a sustainable industrial future.
With our interdisciplinary expertise, modern technologies, and a strong network of partners from science and industry, we are setting new standards in applied research.
Together, we develop solutions that not only deliver today but also shape the future of industry.
From Here, We Take Over
Our Research
BMBF / VDI / VDE-IT / Joint Project: Trust4XChain – Trustworthiness through a Chain of Trust in Data Space-Based Ecosystems for Value Chains
Within the scope of this research project, SEITEC GmbH plays a key role in implementing the overarching IoT/edge infrastructure. High-quality data from electronics manufacturing – accessed via machine control systems – is collected and transformed into standardized submodels of an administration shell (AAS). The IoT infrastructure, inspired by GAIA-X, provides various Federated Services and Trust Services, as well as trusted data spaces in the context of IDS (International Data Spaces).
BMWK / DLR / Joint Project: ESCADE – Energy-Efficient Large-Scale Artificial Intelligence for Sustainable Data Centers Subproject:
The goal of this subproject is the development and technical implementation of software modules for measuring the sustainability of data centers.
BMWK / VDI / Joint Project: NuMA 4.X – Sustainable and Human-Centered Automotive Factory 4.X
NuMA 4.X is developing and testing a modular, AI-based assistance system for employees in vehicle manufacturing, using three automotive use cases at the Ford production plant in Cologne. Subproject: Design and implementation of a hybrid cloud/edge reference architecture for domain-specific acquisition of machine and sensor data, as well as the development of human-centered AI modules for resource-efficient maintenance and quality inspection.
BMWK / AIF / Joint Project: BaSys4iPPS – Integrated Maintenance and Production Planning Through Decentralized Maintenance Forecasting for Legacy Machines in BaSys 4.0
Subproject: Integration of machine data from legacy systems using machine-specific legacy protocols into the BaSys 4.0 framework, utilizing administration shells and edge technologies.
BMBF / PTKA / Joint Project: KausaLAssist – Causal Graphs as a Learning Assistance System for Automated Error Management in Production
Subproject: Decentralized digital twin and AI enablement of production machinery.
BMWi / ZIM Cooperation Project with Fraunhofer IWU Chemnitz
ModulFinger – Development of a Modular and Adaptive Fingerprinting App for Condition Monitoring of Machine Tools Based on Edge Technology
BMWi / DLR / Joint Project: SPAICER – Scalable Adaptive Production Systems Through AI-Based Resilience Optimization
Subproject: SPAICER Platform Architecture – Development of interfaces and software applications for various smart resilience services.
BMWi / ZIM Cooperation Project with Ernst Abbe University of Applied Sciences Jena
Development of an expert system to replicate the cognitive abilities of a machine operator using AI methods. Manual measurements performed by the operator are to be replaced by newly developed autonomous, technical measurement systems.
BMWi / ZIM Cooperation Project with Ernst Abbe University of Applied Sciences Jena
Development of a model-based predictive control (MPC) system for pressure swing adsorption (PSA) plants. This includes the creation of a commissioning and supervision tool for efficient, automated, and guided deployment of the complex MPC control system, as well as runtime monitoring.
BMWi / ZIM Cooperation Project with Fraunhofer Institute for Optronics, System Technologies and Image Exploitation (IOSB), Applied Systems Technology Branch (AST) in Ilmenau
ReWaNet – Intelligent Automation Solution for Resource-Efficient Network Operation and Elevated Tank Management in Drinking Water Systems, Based on a Hybrid Data Model and 24-Hour Forecasting
BMWi / PRO INNO Cooperation Project with the University of Applied Sciences Jena
Neuro-fuzzy software module for biotechnical systems – predictive control and modeling using neural networks.
BMBF / VDI / VDE-IT / Joint Project: Trust4XChain – Trustworthiness through a Chain of Trust in Data Space-Based Ecosystems for Value Chains
Within the scope of this research project, SEITEC GmbH plays a key role in implementing the overarching IoT/edge infrastructure. High-quality data from electronics manufacturing – accessed via machine control systems – is collected and transformed into standardized submodels of an administration shell (AAS). The IoT infrastructure, inspired by GAIA-X, provides various Federated Services and Trust Services, as well as trusted data spaces in the context of IDS (International Data Spaces).
BMWK / DLR / Joint Project: ESCADE – Energy-Efficient Large-Scale Artificial Intelligence for Sustainable Data Centers Subproject:
The goal of this subproject is the development and technical implementation of software modules for measuring the sustainability of data centers.
BMWK / VDI / Joint Project: NuMA 4.X – Sustainable and Human-Centered Automotive Factory 4.X
NuMA 4.X is developing and testing a modular, AI-based assistance system for employees in vehicle manufacturing, using three automotive use cases at the Ford production plant in Cologne. Subproject: Design and implementation of a hybrid cloud/edge reference architecture for domain-specific acquisition of machine and sensor data, as well as the development of human-centered AI modules for resource-efficient maintenance and quality inspection.
BMWK / AIF / Joint Project: BaSys4iPPS – Integrated Maintenance and Production Planning Through Decentralized Maintenance Forecasting for Legacy Machines in BaSys 4.0
Subproject: Integration of machine data from legacy systems using machine-specific legacy protocols into the BaSys 4.0 framework, utilizing administration shells and edge technologies.
BMBF / PTKA / Joint Project: KausaLAssist – Causal Graphs as a Learning Assistance System for Automated Error Management in Production
Subproject: Decentralized digital twin and AI enablement of production machinery.
BMWi / ZIM Cooperation Project with Fraunhofer IWU Chemnitz
ModulFinger – Development of a Modular and Adaptive Fingerprinting App for Condition Monitoring of Machine Tools Based on Edge Technology
BMWi / DLR / Joint Project: SPAICER – Scalable Adaptive Production Systems Through AI-Based Resilience Optimization
Subproject: SPAICER Platform Architecture – Development of interfaces and software applications for various smart resilience services.
BMWi / ZIM Cooperation Project with Ernst Abbe University of Applied Sciences Jena
Development of an expert system to replicate the cognitive abilities of a machine operator using AI methods. Manual measurements performed by the operator are to be replaced by newly developed autonomous, technical measurement systems.
BMWi / ZIM Cooperation Project with Ernst Abbe University of Applied Sciences Jena
Development of a model-based predictive control (MPC) system for pressure swing adsorption (PSA) plants. This includes the creation of a commissioning and supervision tool for efficient, automated, and guided deployment of the complex MPC control system, as well as runtime monitoring.
BMWi / ZIM Cooperation Project with Fraunhofer Institute for Optronics, System Technologies and Image Exploitation (IOSB), Applied Systems Technology Branch (AST) in Ilmenau
ReWaNet – Intelligent Automation Solution for Resource-Efficient Network Operation and Elevated Tank Management in Drinking Water Systems, Based on a Hybrid Data Model and 24-Hour Forecasting
BMWi / PRO INNO Cooperation Project with the University of Applied Sciences Jena
Neuro-fuzzy software module for biotechnical systems – predictive control and modeling using neural networks.
Research-Driven Innovation
Recognized Excellence
Honored by the Stifterverband for German Science
Why SEITEC Is the Right Partner
- Strong Network: Collaborations with leading partners from science and industry for forward-looking research.
- Future Technologies: Technical expertise and application-oriented research in AI, IIoT, edge/cloud technologies, and administration shells.
- Focus on Practical Application: Research projects deliver ready-to-use solutions such as the datAIndustry App and ModulFinger App.
- Funded Innovation: Partner in projects combining technical excellence with social and economic impact.
- Sustainability: Energy-efficient technologies and resource-saving processes promote a sustainable industry.
- Recognized Excellence: Multiple awards for “Innovative Through Research” by the Stifterverband (German Science and Humanities Council).
