DSC – Digital Supply Chain
Welcome to the "Digital Supply Chain" Research Group
We design, develop, test, and implement AI- and IoT-based solutions for manufacturing, logistics, and sustainable value chains. Our goal is to make processes more transparent, efficient, and resilient. To achieve this, we integrate physical processes with operational information systems and data-driven decision-making to support companies through their digital transformation.
Insights into Our Research
Would you like to learn more about our work and stay up to date on the latest news? Follow us on LinkedIn!
There, we regularly take you behind the scenes: We share the latest project results, report directly from our labs, and provide updates on events.
Our Research
Through our research, we work with companies to explore the following questions:
How can data from production and logistics be intelligently collected and used to make better decisions?
How can we achieve seamless information exchange between systems and partners?
How can digital technologies be used to make processes and value-creation systems more efficient, resilient, and sustainable?
Do you have a project idea or need support? We’d be happy to help!
HyConnect Project
A lack of connectivity between H₂ refueling stations and logistics providers makes it difficult to plan supply and demand. HyConnect addresses this with a digital platform for H₂ availability and refueling slot reservations. The goal is to increase planning reliability and competition.
To this end, the DSC research group is developing an ML-based pricing service as well as AI middleware that generates LLM-supported adapters, thereby seamlessly integrating transport management systems with HyConnect.
Approach to a Solution
HyConnect’s technological approach is based on three key pillars that establish a seamless connection between hydrogen infrastructure and logistics:
Central Reservation Platform: At the heart of the solution is a digital platform that enables binding reservations of hydrogen refueling capacity. It serves as a tool for directly balancing supply and demand, thereby significantly increasing planning certainty for logistics companies.
AI-Based Interface Integration: To simplify communication between refueling station operators and freight forwarders, we are developing an interface integration service based on GPT technologies. This service supports the integration of various software solutions and enables efficient, cross-platform data exchange.
AI-Driven Pricing: Machine learning models are used to analyze the price elasticity of hydrogen in order to generate precise price forecasts. This dynamic pricing optimizes the utilization of refueling station infrastructure and increases the economic appeal for all stakeholders.
Mission of the DSC Research Group
The DSC research group is responsible for the requirements analysis and detailed specifications for the AI-based interface service and the pricing service. In doing so, we are researching and integrating groundbreaking technologies such as agent-based LLM workflows to automate and system-independently connect the flow of information between the fueling station infrastructure and freight forwarders. At the same time, our team is designing machine learning models to predict the price elasticity of hydrogen based on data. In addition to the technical implementation of these services, we are also working on defining the semantic data models and designing the operational workflows.
More Information
Funded by the
Ministry of the Environment, Nature Conservation, and Transportation (https://www.umwelt.nrw.de/) in cooperation with the Ministry of Economic Affairs, Industry, Climate Protection, and Energy of the State of North Rhine-Westphalia (https://www.wirtschaft.nrw/ministerium)
Project Sponsor
Project Management Jülich (https://www.ptj.de/)
Project Partners
PEM RWTH Aachen University (https://www.pem.rwth-aachen.de/go/id/fecr/)
H2 Mobility Deutschland GmbH & Co. KG (https://h2-mobility.de/)
MANSIO GmbH (https://www.mansio-logistics.com/)
H2 Green Power & Logistics AG (https://www.h2greenpowerlog.de/)
Contact
move.mORe Project
Multimodal Logistics in the Upper Rhine Region
As part of the move.mORe project, DSC is collaborating with Karlsruhe University of Applied Sciences to support the further development and transformation of logistics for companies in the Upper Rhine region. Together, we are developing an innovation network that bridges research and practice. We are establishing a decentralized logistics campus and implementing pragmatic transfer projects in collaboration with local companies.
Approach to a Solution
The project is based on three closely interlinked pillars.
The “Logistics on the Upper Rhine” innovation network offers local companies a platform for exchange on an equal footing. Together, we identify short-, medium-, and long-term practical logistics challenges. We address these challenges in collaboration with companies and students through short-term implementation projects or long-term research projects.
To do this, we utilize our decentralized logistics campus, which consists of the laboratory infrastructure of both Universities. In the Digital Supply Chain lab of the DSC research group, we work together with companies and students in a real-world setting on technologies and applications for the digitalization of production, logistics, and supply chains. Karlsruhe University of Applied Sciences conducts research in its lab on the interfaces between IT and operational technology.
With our mobile logistics lab, we bring research and technology transfer directly to companies on-site and provide insights into our work at events. The campus is complemented by infrastructure provided by companies, which they contribute either in our labs or at their own locations.
Mission of the DSC Research Group
The DSC research group leads the move.mORe subproject “Multimodal Logistics” and oversees the innovation network. Its responsibilities also include the development and construction of the decentralized campus, which includes the mobile logistics laboratory. The third focus is on implementing the projects that arise from the research roadmap.
More Information
Supported by
a joint initiative of the Federal Ministry of Education and Research and the Joint Science Conference (GWK)
Project Sponsor
VDI Technology Center GmbH, Düsseldorf
Project Partners
Research collaboration between Karlsruhe University of Applied Sciences and Hochschule Offenburg
Official project website:
The DSC research group has already conducted research on the following projects:
KINCHI
AI and Order Processing in the Cloud, with Smart Integration of Tradespeople's Apps
Small businesses often use software solutions that are not connected to one another via interfaces. Manually entering the same data into multiple applications is time-consuming and prone to errors. The KINCHI project solves this problem with a universal cloud platform that seamlessly connects ERP systems and apps and offers additional value to small businesses. The DSC research group is leading the project and is responsible for the reference process, the data model, and AI services for these businesses. With our services, you can easily identify opportunities for process optimization tailored to your specific needs, analyze your company’s performance in dashboards, and access your business data via a chatbot.
Approach to a Solution
Based on a process analysis of skilled trades businesses, a standardized order-processing workflow is defined. This forms the basis for KINCHI’s data model and interface concept, which coordinates data exchange between various software solutions via a central platform. This platform utilizes existing technology standards and offers AI services to support trade-related processes.
Mission of the DSC Research Group
The DSC research group is leading the KINCHI project. It is responsible for developing the reference process, requirements engineering, and the joint development of the platform concept. Based on the platform concept, the DSC research group is also leading the specification of the data model and interfaces, as well as the development of a business model. During the implementation phase, the group’s primary focus will be on developing AI services.
More Information
Funded by the
Federal Ministry of Education and Research
Project Management Agency
Karlsruhe Project Management Agency
Project Partner
Official Project Website
Contact
KINLI
Artificial Intelligence for Sustainable Food Quality
Many people expect meat and sausage products that meet high animal welfare and quality standards. In the KINLI project, we developed a proactive approach: Using artificial intelligence (AI) and data analysis, we predict production challenges before they arise. This reduces waste and helps companies meet high quality and sustainability standards in a cost-effective and affordable way.
Approach to a Solution
A key outcome of the project will be a central data platform that collects all necessary information along the supply chains from many different sources and makes it available for use by AI services. The AI services use the data to alert employees to potential problems and assist them in resolving these issues.
The project focuses on two areas as examples:
In cooked ham production, machine data and images are combined to meet consumer expectations regarding the ham’s appearance and texture while minimizing waste. The AI is designed to optimize machine parameters and provide guidance on meat processing.
In turkey farming, AI is used to analyze images and environmental data to ensure that the birds grow up healthy and safe. Farmers receive alerts about anomalies and can thus take early action to improve animal welfare and health.
Another key part of the project is ensuring that people can actually understand and use the AI’s recommendations, regardless of whether they’ve been in the industry for a long time or are new to it.
Mission of the DSC Research Group
The DSC research group uses data mining to gather the necessary data—which is generated at various points along the supply chain and, when combined, provides insights into the overall process—and analyzes it to identify overarching correlations. This includes, in particular, machine data from ham production and environmental data from turkey farming. The findings are implemented in AI services that generate results that are explainable and comprehensible to employees. In addition, DSC supports the development of the overall concept and the implementation of the data platform. This includes not only various interoperable interfaces but also a holistic data model spanning the entire food supply chain. Demonstrators are being developed for each of the various services to clearly illustrate how they work.
More Information
Funded by
the Federal Ministry of Food and Agriculture pursuant to a resolution of the German Bundestag
Project Sponsor
Federal Agency for Agriculture and Food
Project Partner
Kolsert KG
Official Project Website
Contact
LogIKTram
Logistics Concept and ICT Platform for Freight Transport in Tram and Light Rail Cars
Conventional last-mile deliveries place a strain on roads, the environment, and local residents, while alternatives in local public transit are rarely used. Using Karlsruhe as a case study, the LogIKTram project developed efficient transshipment and transport procedures to utilize light rail for freight transport. To this end, the DSC research group developed a planning model and, together with the project partners, created an ICT platform for planning and executing shipments. A transferable logistics concept, including economic feasibility analyses, supports the planning and evaluation of this idea in other cities as well.
Approach to a Solution
Based on stakeholder interviews, an analysis of the transportation needs of potential goods tram customers, and the local conditions of the light rail network, a logistics concept for the Karlsruhe region will first be developed. This concept will serve as the basis for a model for strategic, tactical, and operational transportation planning. Requirements for the ICT platform will then be derived from the logistics concept and the planning model. In addition, requirements for transshipment and transport procedures will be developed based on the logistics concept. The ICT platform and the transshipment and transport procedures will be implemented and demonstrated as prototypes, and will be tested and further developed in simulation models to assess their feasibility and impact on traffic flows.
Mission of the DSC Research Group
Within the project, Hochschule Offenburg is responsible for developing the logistics concept, the operator and planning model, as well as designing and implementing the necessary software functionalities for freight forwarders and shippers within the ICT platform.
For the requirements analysis, the DSC research group uses transport data from potential Gütertram customers, data from the light rail operator, publicly available data from OpenStreetMap (OSM), and information on local public transit schedules and stops via the General Transit Feed Specification (GTFS). This data is also used to conduct feasibility analyses for the implementation of the concepts.
To implement the functionalities on the ICT platform, the DSC research group adapts existing data formats for planning and booking transports and supplements them with new, specific data formats. These are intended to ensure smooth communication between stakeholders and, consequently, the efficient handling of transportation via the ICT platform.
More Information
Funded by
the Federal Ministry for Economic Affairs and Climate Action, pursuant to a resolution of the German Bundestag
Project Management Agency
DLR Project Management (German Aerospace Center)
Project Partner
MARLO Consultants GmbH
Official project website
Contact
Laboratories
The Digital Supply Chain Lab and the Mobile Logistics Lab offer hands-on experiences with modern supply chains and digital technologies. While the Digital Supply Chain Lab examines and refines processes from supplier to customer using technologies such as RFID, UWB, Industrial IoT, and artificial intelligence, the Mobile Logistics Lab brings research and technology transfer directly to companies and events. This creates flexible demonstration, learning, and development environments for more transparent, efficient, and resilient logistics processes.
Digital Supply Chain Lab
The Digital Supply Chain Lab simulates physical processes, data collection, data exchange, and data-driven applications along a supply chain—from suppliers through manufacturers to customers. It provides a practical learning, demonstration, and development environment for companies, researchers, and students.
In realistic processes, current concepts, digital technologies, and AI-based applications can be tested, evaluated, and developed. At the same time, work on demonstrators in research projects supports the early and targeted development of practical results. In this way, the lab helps make digital supply chains more transparent, efficient, and resilient.
Process Visualization
Demonstrators
Supply Chain: Real-time transparency in a closed-loop container system and throughout the entire order fulfillment process (from supplier to customer) using RFID, UWB, sensor integration, ERP and MES connectivity, and data exchange along the supply chain.
Industrial IoT: Data collection in single-unit production via IIoT, including system integration and interfacing with the supply chain demonstrator.
Circular Economy: Data-driven integration of R-strategies into the supply chain
Project Demonstrators: Hands-on research through interactive demonstrators of our research results tailored to specific target groups.
Offers for Businesses
Companies can use the lab, for example, for the following topics.
Exploring current technologies
Joint development of prototypes and demonstrators for the use of these technologies within their own companies
Integration and demonstration of their own products and solutions
Joint research and development projects
Seminars and training sessions
Offers for Students
The lab offers the following opportunities for students
Exposure to cutting-edge technologies in courses
Student projects
Final theses
Technologies
The technological focus is on
tracking and tracing in supply chains
Real-time location systems (RTLS)
(Industrial) IoT solutions
Artificial Intelligence and Machine Learning
Interfaces and data transmission
Future-Proof IT and Software Architectures
Mobile Logistics Lab
Innovation happens where it’s needed—in your warehouse, at your loading dock, or in your yard. With the DSC Research Group’s mobile lab, we bring technology, expertise, and a passion for experimentation directly to your company.
At its heart is a Renault Master e-Tech that has been fully converted into a research vehicle: emission-free on the road, self-sufficient in operation, and equipped like a stationary lab. This allows us to expand our lab infrastructure with a crucial capability: the ability to set up and test experiments and demonstrators directly in your real-world operating environment.
Everything on board:
Two fully equipped workstations for focused work right on site
Additional batteries for true self-sufficiency, even far from any power outlet
High-performance workstation: computing power for data-intensive applications
Swivel touchscreen for presentations and collaborative work
Full connectivity via 5G, Wi-Fi, GPS, LoRaWAN, and RFID
Workshop equipment and materials for creative team activities
The mobile lab was
acquired as part of “move.mORe – Sustainable Mobility in the Upper Rhine Region,” a joint project of the Universities of Offenburg and Karlsruhe, funded by the federal-state initiative “Innovative University.”
The target
audience consists of companies in the region involved in logistics that want to not only discuss new technologies but also experience and test them firsthand. Contact us—we’ll come by.
Use Cases
The mobile logistics lab opens up new opportunities for knowledge transfer, as it can operate independently of stationary laboratory infrastructure. The vehicle is flexibly configured to accommodate various applications. Among other things, the vehicle can be used for the following use cases:
Capturing and analyzing logistics flows in intralogistics and distribution logistics
Setting up demonstrators and conducting trials for tracking & tracing as well as real-time location systems (RTLS) both indoors and outdoors
Collection and gathering of logistics-related data from project partners or in trials and test setups
Conducting joint workshops directly on-site
Presentation and demonstration of project results to the interested public
Technologies
The vehicle is equipped with a wide range of technologies, including
RFID and UWB hardware with corresponding software, GPS and Galileo-based localization
5G, Wi-Fi, and IoT networks
Storage and servers
Workstations
Workshop materials and an interactive display
Industry
Supply chains in a volatile world require real-time transparency, interconnected IT systems, and reliable forecasts. We support you in optimizing your digital supply chain.
Key Areas:
Strategy: IoT, AI, and digital transformation planning.
Prototypes: AI services and IoT applications for production, logistics, and SCM.
Architecture: Design of interconnected, future-proof IT landscapes.
Software Selection: Independent guidance on the selection and integration of ERP, MES, and IoT platforms.
More Information
Team
Student Employees
Christian Friedrich
Elisa Busam
Jonas Walliser
Lisa Trüschel
Evgeniy Sulimov
Marius Köpke
Lucas Denon
Alumni
Robin Brischle
Jonas Ziegler
Tim Zeiser
Publications
Reviewed Paperes
Pack, C.I.; Zeiser, T.; Beecks, C.; Lutz, T. KINLI: Time Series Forecasting for Monitoring Poultry Health in Complex Pen Environments. Animals 2025, 15, 3180. https://doi.org/10.3390/ani15213180
Tim Zeiser, Alexander Prange, Corinna Köters, Maik Schürmeyer, and Theo Lutz. Parameter Optimization for a Lake Injector. Industry 4.0 Science, 2024, Vol. 40, No. 6, pp. 40–46. https://doi.org/10.30844/I4SD.24.6.40
T. Zeiser, D. Ehret, T. Lutz, and J. Saar, “Explainable AI in Manufacturing,” 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC), Funchal, Portugal, 2024, pp. 1–8, doi: 10.1109/ICE/ITMC61926.2024.10794363.
U. Ertem, T. Lutz, and T. Zeiser, “Bibliometric Analysis as a Means of Efficiently Assessing Trends in Artificial Intelligence,” 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC), Funchal, Portugal, 2024, pp. 1–7, doi: 10.1109/ICE/ITMC61926.2024.10794216.
Ziegler, J.; Menzer, M.; Lutz, T.; Dittrich, I.: Data formats for communication between freight tram operator and forwarder. In: M. Shafik (ed.): Emerging Cutting-Edge Developments in Intelligent Traffic and Transportation Systems: Proceedings of the 7th International Conference (ICITT 2023), Incorporating the 7th International Conference on Communication and Network Technology (ICCNT) (2024) 50, pp. 295–306
Fäßler, Lisa; Dittrich, Ingo; Lutz, Theo; Ziegler, Jonas; Frindik, Roland; Koch, Günter: Logistics Concept for Freight Transport by Tram. Analysis of Logistical Requirements for a Freight Tram Concept, in: Internationales Verkehrswesen 74 (2022) 3, pp. 46–51.
Ziegler, Jonas; Dittrich, Ingo; Lutz, Theo; Fäßler, Lisa: Planning Challenges in Intermodal Transport. Data Models for the Exchange of Planning Data for Regional Freight Transport. In: Industry 4.0 Management 38 (2022) 6, pp. 59–62.
Seifert, Benjamin; Lutz, Theo: Machine Learning in Supply Chain Management. An Overview of Existing Approaches Based on the SCOR Model. In: Industry 4.0 Management 37 (2021) 2, pp. 49–51.
Bruder, Lukas; Neumayer, Dirk A.; Lutz, Theo: Selection Criteria for IoT Platforms. Informed Selection of a Suitable IoT Platform Based on Commonly Used Criteria. In: Industrie 4.0 Management 37 (2021) 4, pp. 55–58.
Knapp, Matthias; Lutz, Theo: Master Data Taxonomy—A Systematic Approach to Assess and Migrate Master Data, 2021 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC), 2021, pp. 1–8, doi:10.1109/ICE/ITMC52061.2021.9570250
Unreviewed Papers
Zeiser, T., Köters, C., Lutz, T., Schürmayer, M., Köppen, L., Prange, A.: KINLI—Optimizing Supply Chains with Artificial Intelligence to Predictively Promote Animal Welfare and Food Safety. In: Der Lebensmittelbrief (2024), May/June, Vol. 35, pp. 48–49
Lutz, T.; Shuvo, S.; Brischle, R.: KINCHI: Smart Digitalization of Order Processing in the Skilled Trades. In: Forschung im Fokus (2023) 26, pp. 43–45
Dittrich, I.; Ziegler, J.; Lutz, T.; Menzer, M.: LogIKTram: Concepts for Regional Freight Transport via Light Rail. In: Forschung im Fokus (2023) 26, pp. 46–49
Lutz, T.; Ziegler, J.; Zeiser, T.: KINLI: Artificial Intelligence for Sustainable Food Quality. In: Research in Focus (2023) 26, pp. 112–113
Sautter, S.; Haigis, N.; Baumert, M.; Lutz, T.: Machine Learning in Production Planning and Control. In: Research in Focus (2022) 25, pp. 78–81
Fäßler, L.; Dittrich, I.; Lutz, T.; & Ziegler, J.: LogIKTram: Sustainable Tram-Based Freight Transport. In: Research in Focus (2022) 25, pp. 66–68
Directions
The entire DSC research group is housed in offices at Schwedenstraße 7 in 77723 Gengenbach, which facilitates seamless collaboration among the individual DSC research divisions. The location offers:
a modern work environment in well-lit rooms
ergonomic workstations with height-adjustable desks
extensive, innovative IT equipment
ample space for personal growth
Job Openings
The DSC Research Group is always looking for student assistants and research associates who are passionate about research and innovation. Doctoral studies are also available in various fields.
Our practice-oriented capstone projects and thesis topics
Practical Final Theses: Final Thesis Topics in the Moodle Course!
Are you looking for an exciting topic for your thesis? In our Moodle course, you’ll find current research questions from our ongoing projects and the lab. Get your thesis off to a strong start with a strong practical focus and excellent guidance!
Click here for the Moodle course: https://elearning.hs-offenburg.de/moodle/course/view.php?id=7832
Note for companies: Do you have an exciting real-world project? We also collaborate on supervising external final theses in our areas of expertise. Feel free to contact us!
Contact