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SAILEX Sales and operations intelligence with explainable AI The project aims to develop an AI-based analysis tool for ERP systems that combines sales data with internal and external factors. This will not only enable general sales trends to be recognised, but also individual correlations, such as discounts or external influences such as weather and political events. This helps to create more precise purchasing forecasts, avoid bottlenecks and reduce excess stock and reduce excess stock, which saves storage costs. In addition, a large language model is also used to explain the AI forecasts in order to ensure the traceability decisions, supported by explainable AI approaches. Contact persons: S. Leohold   (Project manager)Funded by: Land Bremen Duration: 15.02.2025 - 15.08.2026 See project's publications See project's page |
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Prophecy Prognostic Model Selection for Predictive Maintenance and an Integrated Reinforcement Learning-based Production Scheduling in Dynamic Manufacturing Systems This research project is a collaboration between the Bremer Institut für Produktion und Logistik (BIBA) at the University of Bremen, Germany, the Federal University of Rio Grande do Sul (UFRGS), Brazil, the Federal University of Santa Catarina (UFSC), Brazil, and the Federal University of Amazonas (UFAM), Brazil. The goal of this project is to develop a self-adaptive model selection method for predictive maintenance that is fully integrated into production and maintenance planning. To achieve this, a machine learning-based approach will be developed, enabling the automated selection of suitable prognostic models for different system configurations and conditions. A key aspect is the incorporation of reinforcement learning for the dynamic optimization of machine availability and utilization in real time. This is based on a digital representation of the production system, which allows for the evaluation of decision impacts using production logistics KPIs. This performance assessment enables targeted feedback between meta-learning and reinforcement learning, contributing to the continuous improvement of the system. A key aspect of the project is the integration of reinforcement learning to dynamically optimize machine availability and utilization in real time. This is based on a digital representation of the production system, allowing the assessment of decision impacts using production logistics KPIs. The continuous feedback loop between meta-learning and reinforcement learning facilitates the ongoing improvement of the system. To validate the developed methods, a simulation-based environment will be created, which replicates the relevant production and maintenance processes with the required level of abstraction. Finally, the developed system will be tested in two industrial use cases in Germany and Brazil. Contact persons: H. Engbers (Project manager)R. Caballero Gonzalez Funded by: DFG Duration: 01.02.2025 - 31.01.2027 See project's publications See project's page |
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Smartport Living Lab Reactive, intelligent condition monitoring of the harbour superstructure The Smartport Living Lab project addresses the challenges facing Bremen's ports in competition with the North Range ports. The aim is to develop innovative systems for a connected and sustainable port industry in Bremen/Bremerhaven. Flying drones and autonomous mobile robots are key technologies at BIBA for innovative condition monitoring solutions. These technologies are developed and tested in decentralised living labs, supported by a Smart Cooperation Platform that promotes collaboration between the participating research institutions and partners. The project strengthens the sustainable competitiveness and growth potential of the port locations and represents Bremen's innovative strength in maritime logistics. Contact persons: L. Rolfs (Project manager)D. Keiser M. Kreutz C. Petzoldt Funded by: Land Bremen / EFRE Duration: 29.01.2025 - 31.12.2028 See project's publications See project's page |
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LAMAsense INTEK - LAMAsense / Entwicklung eines digitalen Zwillings für die Instandhaltung und einer Service-Plattform als Nutzerschnittstelle Contact persons: M. Kreutz (Project manager)Funded by: BMWK Duration: 01.01.2025 - 31.12.2026 See project's publications See project's page |
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SIM-TWIST Development of a simulation environment for automated terminal operation concepts with special consideration of automated twistlock handling Twistlocks are mechanical locking elements that are used to secure containers on ships. The current manual handling of twistlocks is time-consuming and poses risks to occupational safety. The research project SIM-TWIST investigates how automated twistlock handling systems (ATS) could be used in container terminals. A simulation environment is being developed and used to derive specific recommendations for the use of ATS. The benefit is the reduction of technical and economic risks in the future use of ATS and the promotion of the market maturity of such systems. This can increase efficiency, safety and profitability of container terminals. Contact persons: S. Schukraft (Project manager)Funded by: BMDV Duration: 01.01.2025 - 31.12.2026 See project's publications See project's page |
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NaBeMi Development of a Quality Control Loop-Based Assistance System for Sustainable Resource Planning in Manual and Hybrid Assembly The NaBeMi research project addresses the growing importance of sustainability in consumer behavior and the challenges SMEs face in achieving sustainability goals in production. The aim of the project is to develop a methodology for sustainable resource planning that considers environmental, economic and social aspects. A web-based support system supports the resource planning process for manual and hybrid assembly systems. The methodology integrates three quality control loops to resolve conflicts between traditional and sustainability objectives, enabling comprehensive resource planning. This approach analyzes trade-offs and ensures high quality planning. Contact persons: D. Schweers (Project manager)D. Keiser Funded by: BMWK / IGF Duration: 01.11.2024 - 31.10.2026 See project's publications See project's page |
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Wind-X Conceptualisation, implementation and demonstration of interoperable solutions for traceability and digital twins in the wind industry The Wind-X project aims to promote the wind industry through a data ecosystem for innovative and sustainable wind turbines over their entire life cycle. Experience, technologies and solutions from Catena-X, Gaia-X and other Manufacturing-X initiatives will be transferred to the wind industry. The aim is to develop data-driven solutions and software services specifically for the wind industry. Intelligent wind turbines and components prepared for digitalisation with standard-compliant asset administration shell sub-models are intended to support this. These digital twins will be equipped with configuration and communication capabilities as well as data room connectors. In addition, value-added services (business applications) are being developed that utilise raw data from the supply chain for industry-specific use cases. Connectors and basic services serve as the infrastructure for operating the value-added services and enable interoperable data rooms. This will be demonstrated using the two use cases Traceability for Sustainability and Logistics and Digital Twin in the Production and in the Field for the wind industry. BIBA's main objective is to coordinate and develop these two use cases. In particular, the focus here is on specifying the information requirements, clarifying the framework conditions, defining and deriving business mechanisms and identifying relevant data sources and sinks. Building on this, BIBA and its partners will drive forward the concept development and implementation of sub-models and the data integration of the superordinate data space. BIBA will then support the development of data room services for querying and transferring data from the sub-models for both use cases. BIBA will then develop a demonstrator for both use cases. Contact persons: J. Uhlenkamp (Project manager)E. Broda S. Eberlein M. Franke Funded by: BMWK / NextGenerationEU Duration: 01.11.2024 - 31.07.2027 See project's publications See project's page |
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SanAssist Development of AI speech intelligence for customer service in the sanitary sector within BIM framework The SanAssist project aims to significantly improve the digitalization of customer service in the sanitary sector through innovative methods of optical image and video analysis, as well as AI-based voice solutions. In light of the existing shortage of skilled workers, an intelligent system is being developed that automates the processing of customer inquiries and increases efficiency by handling simple queries and tasks through automated responses, cost estimates, and product suggestions at the Level 1 support level. The BIBA sub-project includes the preliminary classification of email attachments as well as image-based object recognition of SHK parts. By integrating multiple technologies such as machine learning and image-based object recognition, a novel workflow is created that enables the automated extraction of text and image information. Expert evaluations and customer surveys conducted in collaboration with project partners will ensure the quality of the developed solution with the aim of sustainably optimizing customer service and interaction in the sanitary sector. Contact persons: H. Stern (Project manager)W. Zeitler Funded by: BMWK Duration: 01.11.2024 - 31.10.2026 See project's publications See project's page |
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La2-Mo2 Development of an LLM pipeline for processing and transforming natural language commands into context-dependent robot commands The assembly industry faces increasing product variety and customization, which demands production flexibility, complicating Cobot automation, especially for SMEs. Despite Cobot market growth, frequent reconfiguration remains a challenge. Natural language programming could simplify this, but current models lack contextual understanding and precision. The La2-Mo2 project aims to develop a system that uses LLMs for programming Cobots through natural language. By interpreting spoken instructions and converting them into precise robot commands, the system will make Cobot programming more accessible, reducing complexity and increasing flexibility, particularly benefiting SMEs in assembly processes. Contact persons: J. Liebchen (Project manager)N. Meusel C. Petzoldt Funded by: BMWK Duration: 01.10.2024 - 30.09.2026 See project's publications See project's page |
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iCRANE Development of a mobile assistance system to increase the safety of heavy-duty cranes by means of sensory and optical monitoring and verification of assembly The use of cranes is planned on a customer-specific basis and therefore order-related. The selection and overview of the availability of attachments at the depot or across several operating sites depends on the crane rental company's experience and individual inventory management. On the construction site, the delivery, positioning and assembly of the crane components requires a great deal of coordination. The load-bearing capacity of the crane depends in particular on the correct assembly of the attachments, which must be carried out in accordance with the previous planning of the crane deployment. Incorrect assembly jeopardizes the safety of the crane operation and, in the worst case, can lead to the crane toppling over. With this in mind, this project is developing a mobile assistance system to increase crane safety and support the coordination of employees at the depot and on the construction site. The system is divided into three sub-areas: (1) optimization of component control at the depot and construction site, (2) verification of the planning-compliant design of a mobile crane with regard to operational safety and (3) recording and analysis of loads on individual components. Contact persons: H. Engbers N. Jathe S. Oelker M. Quandt Funded by: BMWK Duration: 01.09.2024 - 31.08.2026 See project's publications See project's page |
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SENSOMAI Sensor-supported AI-based benchmarking platform for the human-centred and economical selection and introduction of support systems in intralogistics processes Companies need to improve their production and intralogistics processes due to rising costs and increasing demands for flexibility. This requires a comprehensive process analysis, which is very time-consuming. Small and medium-sized enterprises (SMEs) in particular struggle to select suitable technologies for intralogistics solutions. The goal of the SENSOMAI project is to develop a user-friendly data platform that supports SMEs in selecting and implementing intralogistics systems. This platform utilizes motion data collected by sensors and analyzes it using a deep learning method. The platform identifies optimization potentials and suggests appropriate intralogistics solutions. A before-and-after comparison allows the evaluation of improvements within the company. The platform continuously enhances its recommendations through the validation of results. SENSOMAI is an innovative solution that offers technology-neutral selection options and addresses multiple user groups. Contact persons: L. Rolfs (Project manager)N. Hoppe M. Quandt Funded by: BMBF Duration: 01.08.2024 - 31.07.2026 See project's publications See project's page |
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PassForM2 Process-Driven Adaptation of Agent-Based Control for Modular Assembly Systems The shift from mass production to customized manufacturing presents immense challenges for companies, particularly in assembly, which accounts for more than half of the production time and 20% of the costs. For small and medium-sized enterprises (SMEs), easily scalable solutions are essential. SMEs benefit especially from flexible systems, as these allow them to adjust their production processes efficiently without investing in expensive, specialized equipment. PassForM2 develops an innovative control system for modular assembly systems that can adapt flexibly to changing requirements. In addition to assembly, other systems such as automated guided vehicles (AGVs) can be seamlessly integrated. Through interchangeable hardware modules and decentralized control, we increase efficiency, reduce production costs, and ensure greater resilience against system failures. This technology helps SMEs achieve sustainable small-batch and series production while enhancing their competitiveness by enabling them to respond cost-effectively and adaptively to market changes. Contact persons: B. Vur (Project manager)A. Heuermann Funded by: BMWK / IGF Duration: 01.08.2024 - 31.07.2026 See project's publications See project's page (https://passform.biba.uni-bremen.de/ ) |
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SenZel Development and implementation of AI-supported monitoring and analysis technologies for rotary valves Rotary valves are used in industrial plants for shutting off, discharging or volumetric dosing of bulk materials. They prevent dust and gases from escaping. Maintenance poses a challenge, as rotary valves are subject to heavy wear and are usually not easily accessible. The aim is to increase efficiency by reducing downtimes and optimising maintenance costs with artificial intelligence. Contact persons: M. Lütjen (Project manager)Funded by: BMWK / IGF Duration: 01.07.2024 - 30.06.2026 See project's publications See project's page |
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RIG Robotics Institute Germany The Robotics Institute Germany (RIG) connects leading robotics locations across Germany into a decentralized research network to enhance the international visibility of German robotics research. Research is coordinated through a joint roadmap and research clusters that address the needs of both industry and society. Additionally, a shared research infrastructure is being established. Specialists are trained through targeted education and training programs, robotics benchmarks and innovation competitions are developed, and measures to support start-ups and industry transfer are initiated. RIG strengthens the global reputation of "made in Germany" robotics and unlocks potential through the use of robotic systems in new applications. Contact persons: C. Petzoldt (Project manager)Funded by: BMBF Duration: 01.07.2024 - 30.06.2028 See project's publications See project's page (https://www.robotics-institute-germany.de/) |
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ForkLoad Autonomous pallet loading using an external sensor and control system for retrofitting forklift trucks The aim of the project is to develop a retrofittable system to enable conventional electrically powered forklift to load pallets autonomously. BIBA is developing an external multi-sensor system and algorithms for vehicle and loading control, which communicates with a control module that will be integrated into the forklift. Contact persons: A. Börold (Project manager)J. Liebchen Funded by: BMWK Duration: 01.07.2024 - 30.06.2026 See project's publications See project's page |
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SMART Dynamic control of collaborative assembly in the digital twin using AR and AI-based situation recognition The goal of the SMART cooperation project is to develop an overall system for the dynamic control and task allocation of collaborative assembly processes. For this purpose, the implementation of an AI-based situation recognition using AR devices, which, together with a software platform for dynamic work planning, forms the basis for intelligent and collaborative process and robot control. An AR visualization is being developed for the direct involvement of employees, which shows the process planning and the planned robot actions in real time and thus enables close human-robot collaboration. A digital twin is used to integrate, simulate and control all subsystems. Contact persons: C. Petzoldt (Project manager)D. Keiser Funded by: BMWK Duration: 01.06.2024 - 31.05.2026 See project's publications See project's page |
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ImmoAR Augmented reality system for realistic on-site visualisation of industrial property projects using special tablets and WebAR technology The ImmoAR project aims to create an innovative AR framework with specially developed hardware to simplify the communication of industrial property. The central component is the development of a special tablet with a high-precision AR display. In addition, an AR application is being developed in Python to display visualisations and planning statuses. Another focus is on optimising a web display and implementing an efficient interface to the AR application in order to support complex 3D models. The application is designed for the communicative mediation of commercial property in order to ideally adapt the AR software and improve the GeoAR functionalities. Contact persons: R. Leder (Project manager)W. Zeitler Funded by: BMWK Duration: 01.04.2024 - 31.12.2025 See project's publications See project's page |
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MycelCycle Integrated material, process and product development methodology for product life-cycle optimized mycelium-based packaging products as part of circular economy Sustainable and closed material cycles made from biogenic and recycled resources are becoming increasingly relevant as raw materials become limited. The goal of the project is to develop an integrated methodology for the material, process, and product development of mycelium composite materials using the example of cooler boxes. Mycelia has the potential to transform biomass with its thread-like hyphae into compact structures in just a few days. The project addresses current challenges in the product life cycle in order to design optimized material cycles using mycelium technology. The research framework includes the use of AI-based methods for identifying material combinations and for quality assurance. Contact persons: B. Pupkes (Project manager)M. Hoff-Hoffmeyer-Zlotnik M. Trapp Funded by: Volkswagen Stiftung Duration: 01.02.2024 - 31.01.2028 See project's publications See project's page |
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AutoLog Development of autonomous driving processes and dynamic storage and logistics concepts on automotive terminals The logistics services provided by seaports and inland ports are crucial for German imports and exports and for the global distribution chains of the German automotive industry. Vehicle compounds serve as hubs that are an integral part of the German automotive industry's finished vehicle logistics. Despite this central role, vehicle compound operators face challenges such as increasing handling volumes, limited terminal space, staff shortages and growing demands for efficiency and flexibility. The AutoLog research project aims to explore and realise optimisation potential through the use of automated driving at vehicle compounds. The project aims to increase the efficiency and flexibility of terminal operations through technological developments for the digitalisation of processes and the automation of driving movements. The main objectives of the project are Suitability of automated driving at vehicle compounds: Investigation of the process and infrastructure requirements at the vehicle compound for the successful implementation of automated driving. Technical infrastructure and sensors: Developing the design of the technical infrastructure and sensor technology to ensure robust and safe vehicle control. Human-machine interactions: Investigating how human-machine interactions can be designed to enable intuitive and safe interaction between automated and non-automated processes. Optimisation potential for storage and logistics processes: Identification of optimisation potential for related storage and logistics processes through the introduction of automated driving. By specifically researching and implementing these objectives, the AutoLog project aims to overcome the challenges of vehicle compounds and sustainably improve the future of finished vehicle logistics. Contact persons: M. Hoff-Hoffmeyer-Zlotnik (Project manager)R. Caballero Gonzalez S. Leohold L. Panter L. Rolfs Funded by: BMDV Duration: 01.01.2024 - 31.12.2026 See project's publications See project's page (https://www.autolog-projekt.de/) |
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OffshorePlan II Complementary application of mathematical and discrete-event models to solve complex planning and control problems in offshore construction logistics Offshore construction logistics for wind farms define a complex planning and control problem for which there are no established methods. Discrete-event simulation methods or mathematical optimizations are used, which offer their advantages and disadvantages in terms of runtime, level of detail, and optimality constraints. After the first project phase has laid the foundations in different models and a transformation framework, the second phase focuses on complementary use. In addition to increasing the problem complexity, a cascading framework will be developed that selects suitable model variants and combines them concerning necessary levels of abstraction. Contact persons: M. Lütjen (Project manager)D. Rippel Funded by: DFG Duration: 01.01.2024 - 31.12.2025 See project's publications See project's page |
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Adapt2Mount Development of a health-promoting assembly workplace with adaptive material provision and individual ergonomic optimization As part of the research project, a health-promoting assembly system is being developed for individual ergonomic optimization with adaptive material provision. A sensor system consisting of wearables and cameras records relevant data during work. The central element uses a digital twin that maps a 3D simulation of the work process, including human and assembly system models based on the recorded actual data. Based on the data, ergonomic optimizations are made, whereby the assembly station is initially set up, and the material arrangement is continuously dynamically adapted to the process execution of the individual employee during assembly. Contact persons: R. Leder (Project manager)N. Hoppe D. Rippel Funded by: BMWK Duration: 01.09.2023 - 31.08.2025 See project's publications See project's page |
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ErgoKI Detection and AI-based analysis of ergonomic data in manual assembly using wearbles and machine vision techniques The primary objective of the envisaged project ErgoKI is the development of a system designed for the acquisition and AI-driven analysis of ergonomic data within the context of manual assembly, employing wearables and machine vision techniques. Through the utilization of various sensors and the development of an underlying data layer, a process modelling is carried out which enables the analysis of ergonomics and productivity within the domain of assembly. The key performance metrics are visualised within an intuitive human-machine interface and individual suggestions for improvement are derived. This helps to develop a better understanding of the individual requirements of employees and to implement ergonomic improvements in a more targeted manner. Contact persons: B. Vur (Project manager)J. Liebchen D. Schweers Funded by: Land Bremen Duration: 01.09.2023 - 31.07.2025 See project's publications See project's page |
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MaxMaintain Development of AR-based teleservices and intelligent job scheduling using diagnostic condition monitoring for the efficient maintenance of decentralized wastewater treatment plants The research project aims to develop a planning and control platform for personnel deployment to maintain small wastewater treatment plants. On the one hand, the platform will be used for the central recording and provision of customer and plant data for mobile employees and the central planning of orders and job offers. Specifically, the AR-based remote maintenance functionalities will support staff and customers in identifying, diagnosing, and documenting faults. In addition, using robust maintenance strategies, the platform will achieve a more even utilization of staff and avoid order peaks. Contact persons: D. Rippel (Project manager)A. Ait Alla W. Zeitler Funded by: BMWK Duration: 01.09.2023 - 31.08.2025 See project's publications See project's page |
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DigiKleb Digitization of gluing processes in the automotive industry Within the framework of the sub-project, research is being conducted on the development of methods and procedures for the analysis and prediction of system behavior, for example, in order to identify causes of quality deviations and to propose quality measures. For this purpose, the interdependencies are modeled first qualitatively and then quantitatively by means of so-called effect networks, whereby the data standards of the Asset Administration Shell and OPC-UA are used as a basis in order to establish compatibility and direct system integration in the digital twin. Contact persons: M. Kreutz M. Lütjen Funded by: BMWK Duration: 01.08.2023 - 31.07.2026 See project's publications See project's page |
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RessourcE Developing human resources in service work A competence center for logistics and health-related services will be established in the project in collaboration with practitioners and scientists. RessourcE intends to initiate sustainable transfer structures between research and practice and develop innovations for effective work design, leadership and opportunities for human resource development in the field of low-qualified work. Technical solutions for ergonomic work design and diversity-oriented competence development in low-qualified work are developed, piloted and tested regarding broad applicability. These solutions include, for example, assistance systems for physical work, concepts for supporting mental health, or software tools for systematic selection of suitable assistance technologies. Contact persons: B. Pupkes (Project manager)N. Hoppe L. Panter C. Petzoldt B. Vur Funded by: BMBF Duration: 01.07.2023 - 30.06.2028 See project's publications See project's page |
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MDZ-HB-OL Mittelstand-Digital Centre Bremen-Oldenburg The Mittelstand-Digital Centre Bremen-Oldenburg pursues the goal of increasing the level of digitalisation of SMEs in the Northwest Metropolitan Region through individual support measures. In addition to the classic manufacturing industry and production-related services such as logistics, the focus is also on the consumer-oriented service industry, such as tourism, gastronomy or the creative industry. The participation of the BIBA enables, among other things, the transfer of knowledge from the research projects to industry, the implementation of infrastructure and demonstrators, as well as the implementation of local events and online formats. Contact persons: A. Himstedt M. Knak A. Seelig M. Teucke S. Wiesner Funded by: BMWK Duration: 01.04.2023 - 31.03.2026 See project's publications See project's page (http://digitalzentrum-hb-ol.de) |
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Pakur AI-based counting, classification and inspection of palletized packages during goods receipt and inventory using optical methods on mobile devices Incoming goods inspection is still done manually in many SMEs. Automation of these processes optimizes incoming goods, reduces errors along the entire supply chain and creates competitiveness in the market for transport and warehouse logistics. The implementation of this automation, be it through own development or use of existing solutions on the market, is very costly and not feasible for many SMEs. This is where the research project "Pakur" comes in, in order to enable SMEs in the logistics segment to implement (partially) automated data acquisition in incoming goods inspection or inventory. Recent breakthroughs in the field of image processing using neural networks are to be used to develop an easy-to-use, automatic, digital standard solution for identifying and counting packages based on images of the palletized goods. In doing so, the employee is to be supported by an app in order to accelerate the process of receiving and inventorying goods while minimizing potential errors. Here, algorithms are to be developed and neural networks trained that are capable of recognizing the individual elements, such as packages or bags, on a pallet without error, even in heterogeneous environments, analyzing their packing pattern and then deriving the number of elements correspondingly per unit load. This information can then be passed on directly to a possible inventory management system. Errors are thus detected at an early stage and incorrect information in the system is avoided. The focus of the development is on the creation of the algorithms, based on current, innovative research. The transfer into practice is realized by a ready-to-use, open source software library that can be easily used by third parties and an open source demo application for the smartphone. This ensures that third parties can also actively use the result and apply it to other areas. Contact persons: N. Jathe (Project manager)Funded by: BMWi / AiF Duration: 01.02.2023 - 31.05.2025 See project's publications See project's page (https://pakur.biba.uni-bremen.de/) |
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RaRe2 Human-centred Rapid Reconfiguration of Production and Value Chain in Fast Changing Scenarios The European production landscape is facing major challenges that require sustainable and robust, but at the same time, highly efficient production systems that have the ability to respond to significant changes at high speed. The global objective of the project RaRe2 is to create a flexible and resilient ecosystem platform enabled by the interaction of many European organizations that cooperate in the fast reconfiguration of process chains through collaborative systems and adaptable workforce upskilling. In the project, digital twins of production and logistics systems augmented with forecasting, reconfiguration and optimization functions will be developed at different hierarchical levels along the entire value chain. In addition, methods for flexible and robust workforce planning will be developed. In the next step, the developed methods will be integrated in an ecosystem platform. This research has been funded by the European Union's Horizon Europe Framework Programme (HORIZON) under project reference HORIZON-CL4-2022-TWIN-TRANSITION-01. Contact persons: S. Eberlein (Project manager)K. Burow K. Hribernik S. Schukraft J. Uhlenkamp Funded by: EU Duration: 01.12.2022 - 31.05.2026 See project's publications See project's page (https://raresquare.eu/) |
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hyBit Hydrogen for Bremens industrial transformation The hyBit project plays a important role in the realization of the EU's goal of a climate-neutral economy by means of green hydrogen in a holistic energy transition. The overarching question of the project is: How can climate neutrality be achieved through the targeted technical, economic, ecological, legal and social design of hydrogen hubs? In five steps, pilot applications are defined via flexible modeling of logistics systems that run on hydrogen. For this purpose, transformation paths, infrastructure concepts and roadmaps will first be developed and simulated. The results and simulation performance will be made available to a central transformation platform, which will combine them with the results of other issues beyond mobility and logistics. Contact persons: L. Steinbacher (Project manager)A. Ait Alla E. Broda D. Keiser S. Oelker M. Teucke Funded by: BMBF Duration: 01.09.2022 - 28.02.2026 See project's publications See project's page (http://hybit.org) |
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LogDynamics Bremen Research Cluster for Dynamics in Logistics LogDynamics is a cooperating network of research groups from Universities and research institutes in Bremen. It provides research on logistics topics, an international doctoral training program, and transfer of technology between academia and industry. LogDynamics acts in the areas of logistics management and business processes, computer science and information technology, mathematics, and electrical and production engineering to solve logistics challenges in an interdisciplinary and cooperative manner. Contact persons: A. Himstedt (Project manager)Funded by: Land Bremen Duration: 01.01.2021 - 31.12.2026 See project's publications See project's page (https://www.logdynamics.de) |
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EIT Manufacturing EIT Manufacturing The manufacturing industry is facing major challenges due to increasing global competition, low-cost production in developing countries and scarce raw materials. EIT Manufacturing is an initiative of the European Institute of Innovation and Technology (EIT), in which BIBA is one of 50 core partners. EIT Manufacturings mission is to bring European manufacturing actors together in innovation ecosystems that add unique value to European products, processes, services and inspire the creation of globally competitive and sustainable manufacturing. To do so, the initiative has six strategic objectives: 1. Excellent manufacturing skills and talents: adding value through an upskilled workforce and engaged students. 2. Efficient manufacturing innovation ecosystems: adding value through creating ecosystems for innovation, entrepreneurship and business transformation focused on innovation hotspots. 3. Full digitalization of manufacturing: adding value through digital solutions and platforms that connect value networks globally. 4. Customer-driven manufacturing: adding value through agile and flexible manufacturing that meets global personalized demand. 5. Socially sustainable manufacturing: adding value through safe, healthy, ethical and socially sustainable production and products. 6. Environmentally sustainable manufacturing: adding value by making industry greener and cleaner. EIT Manufacturing aims for the following goals by 2030: Create and support 1000 start-ups 60% of manufacturing companies adopt sustainable production practices EUR 325 million investment attracted by EIT Ventures 50 000 people trained and up- or re- skilled Create 360 new solutions 30% of material use is circular Contact persons: P. Klein (Project manager)K. Hribernik Funded by: European Institute of Innovation & Technology (E Duration: 01.01.2019 - 01.01.2026 See project's publications See project's page (https://eitmanufacturing.eu/) |
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ReaLCoE Next Generation 12+MW Rated, Robust, Reliable and Large Offshore Wind Energy Converters for Clean, Low Cost and Competitive Electricity Offshore wind energy is a key technology for generating renewable energies. Due to its complex processes regarding installation, operation and service, and therefore relatively high costs, offshore wind energy converters still cannot compete with todays energy market prices. To create a competitive offshore WEC with a Levelised Cost of Electricity (LCoE) target of 35/MWh ReaLCoE takes a holistic approach and scrutinises costs in each link of the value chain. As a key element of ReaLCoE, BIBA focusses on the digitisation of future offshore WECs and their adhered value chain. Besides the integration of sensors and the implementation of a condition-based monitoring system, the digital representation of the WECs through a digital twin (product avatar) takes a major part in BIBAs contribution to ReaLCoE. Building on this, a concept for predictive maintenance will be developed and realized. Furthermore, BIBA will develop optimised logistic and installation concepts and will conduct various performance simulations for a further reduction of supply chain and installation costs. To validate the concept, a technology platform for a first prototype of a digitised 12+MW turbine as well as a pre-series array of 4-6 WEC will be installed, demonstrated and tested. Contact persons: K. Burow (Project manager)J. Uhlenkamp A. Ait Alla K. Hribernik S. Oelker Funded by: EU Duration: 01.05.2018 - 31.01.2026 See project's publications See project's page (realcoe.eu) |
