Current Projects

	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: D. Niermann Funded by: BMWK Duration: 01.10.2024 - 30.09.2026 See project's publications See project's page
	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
	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
	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: A. Heuermann J. Wilhelm 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/ )
	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
	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/)
	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. Niermann Funded by: BMWK Duration: 01.06.2024 - 31.05.2026 See project's publications See project's page
	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) Funded by: BMWK Duration: 01.04.2024 - 31.12.2025 See project's publications See project's page
	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. Trapp Funded by: Volkswagen Stiftung Duration: 01.02.2024 - 31.01.2028 See project's publications See project's page
	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/)
	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
	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
	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) D. Schweers Funded by: Land Bremen Duration: 01.09.2023 - 30.04.2025 See project's publications See project's page
	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
	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
	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 C. Petzoldt Funded by: BMBF Duration: 01.07.2023 - 30.06.2028 See project's publications See project's page
	KoMAR Development of an AR-based multi-user system for the potential assessment of collaborative assembly scenarios The KoMAR project is developing a flexible Augmented Reality (AR) multi-user application that connects digital models with real objects. Several people can interact simultaneously in an AR 3D scenario. The goal is context-based and robust interaction in virtual space. The project aims to develop new multi-user functions, such as location-independent participation in AR conferences and joint manipulation of virtual objects. For this, BIBA is developing a potential assessment of collaborative robots in industrial assembly as a first use case. Here, AR enables the early involvement of planning and assembly personnel in a real context without physical system adaptations. Contact persons: L. Rolfs (Project manager) J. Wilhelm Funded by: Land Bremen Duration: 01.06.2023 - 30.11.2024 See project's publications See project's page
	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)
	CompactedCooler Development of a compactable and evacuable insulated container for frozen food shipping Food, especially chilled and frozen, is increasingly ordered online and must be shipped to customers while complying with the cold chain. The polystyrene or EPS boxes that are used nowadays for shipping of chilled and frozen goods, offer good technical properties, such as insulation or food safety, but have ecological disadvantages, not least because of the fossil raw materials. In order to improve the environmental balance of food transportation, the project is being developing an innovative packaging solution that consists largely of recyclable or bioplastics and uses insulating effects of a vacuum. In addition, an efficient return in terms of reusability is strived through a compactable design. Contact persons: M. Trapp (Project manager) Funded by: Land Bremen / EFRE / PFAU Duration: 01.04.2023 - 31.03.2025 See project's publications See project's page
	OptiAssist AI-based anomaly and cause analysis of assembly process data to derive process and assistance system improvement proposals Assembly assistance systems store data for quality assurance. Data analysis of process steps that can lead to production errors through error propagation does not exist yet. OptiAssist develops an AI-based system for identifying anomalies in the assembly process through unsupervised learning; after that, the effort of the assembly operations is reweighted in the priority graph. Based on optimization, an expert system suggests process changes to the process planner on appropriate dashboards. To increase user acceptance, strategies are developed for a suitable time to reschedule the assembly process. Contact persons: D. Schweers (Project manager) H. Engbers Funded by: Land Bremen / FEI Duration: 01.04.2023 - 30.12.2024 See project's publications See project's page
	AITeach Automatic Interpretation and Creation of Assembly-Processes from Demonstration In AITeach, an innovative system is being developed that automates the creation of assembly sequence plans and instructions for assembly assistance systems in the context of work preparation in variant-rich assembly. For this purpose, an innovative software system is to be developed that analyzes sensor data using intelligent algorithms and AI methods with regard to the demonstrated activities. The goal is the automatic recognition of manual assembly work steps, an easy-to-understand preparation and presentation of the recognized activities by means of text-based instructions as well as a visualization based on a digital twin. Contact persons: D. Niermann (Project manager) C. Petzoldt Funded by: BMWK Duration: 01.03.2023 - 28.02.2025 See project's publications See project's page
	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) B. Staar 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/)
	SYDITIL SYstemic DIgital Twins for Industrial Logistics In the SYDITIL project, a systemic digital twin (DT) for logistics is being developed. The technological basis is ?, a language and method for describing complex socio-technical systems, and the WorldLab software. Based on the application scenarios warehouse logistics and port logistics the DT will be developed and evaluated. The intended solution will help to continuously improve the logistics processes. For this purpose, the DT is constantly updated with data gathered from the logistics systems and simulates possible scenarios as well as forecasts upcoming risks. If necessary, the DT sents alerts to control and monitoring systems to optimize logistics operations. In addition, the visualization of simulation and forecast results supports decision-making for future planning. Contact persons: H. Engbers (Project manager) Funded by: EU Duration: 01.01.2023 - 31.12.2024 See project's publications See project's page
	safetyDrone intelligent work safety using autonomous indoor UAVs in ship construction In this project we develop an autonomous indoor blimp drone for safety hazard detection in shipyards. Due to the highly dynamic work environment of the ships construction site, shipyards are subject to an increased risk of accidents. In an extension to the current state of the art, the blimp-based drone system will drastically increase flight times while decreasing noise levels. The risk of additional harm from the drone is close to zero due to the lightweight construction. To ensure robust identification of safety hazards we develop an optical sensor system which uses state-of-the-art AI algorithms for detection. Contact persons: B. Staar (Project manager) Funded by: BMWi / AiF Duration: 01.01.2023 - 31.12.2024 See project's publications See project's page
	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. Hribernik J. Uhlenkamp Funded by: EU Duration: 01.12.2022 - 31.05.2026 See project's publications See project's page (https://raresquare.eu/)
	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: S. Oelker (Project manager) A. Ait Alla E. Broda L. Steinbacher M. Teucke Funded by: BMBF Duration: 01.09.2022 - 28.02.2026 See project's publications See project's page (http://hybit.org)
	AR Improve Development of a guideline for the human-oriented use of AR-based assistance systems in intralogistics Intelligent and interactive AR-based assistance systems have great potential for supporting intralogistics work processes. Still, they have only been used occasionally in this form in practice, especially in SMEs. The object of the AR Improve research project is intelligent and interactive AR assistance systems that combine current AR hardware with sensor technology and image-processing methods. By providing an interactive guide, which is being developed together with SMEs, decision-makers can make well-founded decisions about the needs-based and human-oriented use of AR assistance systems without detailed knowledge of AR technology. Contact persons: M. Quandt (Project manager) M. Kreutz H. Stern Funded by: BMWi / AiF Duration: 01.09.2022 - 31.12.2024 See project's publications See project's page (https://ar-improve.biba.uni-bremen.de/)
	HybridCPPS Human Factors in Hybrid Cyber-Physical Production Systems Many production processes in industry are changing towards cyber-physical systems in which physical and computational elements as well as human operators are interconnected. As a result, human work in production is undergoing profound changes toward collaboration with automated and autonomous systems and their monitoring. In such hybrid cyber-physical production systems (CPPS), the quality of collaboration and interaction between the human operator and technical systems is a key success factor. Hybrid CPPS require an integrated system design consisting of technical, organizational and human-centered viewpoints to ensure their successful implementation and usability. Consequently, the goal of the project is to contribute to the integration of human factors in hybrid CPPS. Interdependencies between the quality and performance of human work and the design of hybrid CPPS are determined and used to derive design principles for planning and redesign of work systems. A demonstrator is to be built that serves as a platform for conducting studies with participants within a model hybrid CPPS. It contains several workstations that represent different processing steps and can be used flexibly as manual or automated workstations. Thus, different variants of hybrid CPPS can be modeled and investigated with regard to their effects on the system performance and on the operators. The results are used to determine the underlying relationships between different design variants and key figures for system performance and the perception of work. Contact persons: H. Stern (Project manager) Funded by: Universit�t Bremen (Zentrale Forschungsf�rderung) Duration: 01.01.2022 - 31.12.2024 See project's publications See project's page
	MEXOT Intelligent work ergonomics using sensory exoskeletons and autonomous transport systems for enhanced human-technology interaction in automotive cargo handling The cargo handling environment in ports is characterized by the handling of heavy and large loads, in which humans are essential despite the progress of automation. In the specific application of automobile handling, the vehicles are prepared for the respective target market in technical centers. For this purpose, tires and trailer couplings, for example, have to be moved and mounted by humans. In addition, there is a large number of additional car parts that have to be picked and, in some cases, assembled in an overhead position. As a result, a high physical strain is placed on the employees, which leads with increasing age to a degree of physical impairment. Within the scope of the project MEXOT, the challenges identified are addressed with a socio-technical development approach. To this end, the use of exoskeletons is targeted, aiming to research on intelligent work ergonomics, which examines human-machine interaction in combination with exoskeletons and automated guided vehicles (AGVs). Motion sensors will be integrated into a passive exoskeleton to track the movement patterns of the employees. First, this information is used to enrich data for an external incentive system that rewards employees for wearing the exoskeleton correctly and integrates gamification approaches to increase motivation. In a second step, the data and process information are used to activate or deactivate individual "elastomeric muscles", aiming at a higher wearing flexibility for activities that do not require physical support. In the third step, the movement information of the exoskeleton will be used to develop a sophisticated pick- and assembly-by-motion concept, which, in combination with the camera system of the AGV, enables the registration of individual work steps in picking and assembly. For the AGV, further research is conducted on increasing productivity and reducing the workload of employees through process-specific and worker-individualized material supply. Moreover, voice- and gesture-based functionalities are implemented for human-machine interaction with the AGV. Contact persons: C. Petzoldt (Project manager) N. Jathe D. Niermann L. Panter M. Quandt L. Rolfs B. Vur Funded by: BMDV Duration: 01.01.2022 - 31.12.2024 See project's publications See project's page (https://www.mexot-projekt.de/)
	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: K. Hribernik P. Klein J. Wilhelm 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/)
	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)