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AI-Consult Multimodal, AI-supported cognitive information support system in logistics processes The aim of the project is to develop an off-the-shelf system for the most intuitive access possible to complex information through natural and low-threshold communication in combination with optical image recognition processes. At the same time, it shall provide experienced users with direct, fast and contactless access to a wide range of functions. For data protection reasons, personal image and voice data will be processed by an integrated computing unit. Contact persons: A. Börold   (Project manager)D. Schweers Funded by: BMWK Duration: 01.04.2022 - 31.03.2024 See project's publications See project's page |
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AKAMAI ASRS New Intralogistics warehouse system AKAMAI team develop a novel Automated Storage and Retrieval System (ASRS) solution, managing non-standard loads efficiently in compact warehouses. This EIT project focuses on an innovative system of vertical displacement (specific elevator) combined with proprietary Autonomous Mobile Robots (AMR) to provide higher density than existing industrial solutions. Contact persons: D. Schweers (Project manager)J. Wilhelm Funded by: EU - EIT Manufacturing Duration: 01.01.2022 - 31.12.2022 See project's publications See project's page |
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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: Universität Bremen (Zentrale Forschungsförderung) Duration: 01.01.2022 - 31.12.2024 See project's publications See project's page |
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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 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/) |
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RIEMANN ROS-based Education of Advanced Motion Planning and Control This project aims at reducing technological barriers towards using a fleet of robots in warehouses and conventional manufacturing environments. This project creates learning material to upskill university students and professionals in advanced autonomous navigation concepts, specifically how to leverage existing open-source software libraries on mobile robot platforms. From end-user perspective, our education materials will help industries using mobile robot solutions to perform complex debugging/maintenance without overly relying on their third-party supplier. This will save time spent tuning motion planning libraries without being fully aware of the effect of underlying hyperparameters. Contact persons: T. Sprodowski (Project manager)Funded by: EU - EIT Manufacturing Duration: 01.01.2022 - 31.12.2022 See project's publications See project's page |
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PaLA Palletized Loads Automatic Loading System for unmodified European Trailers to enable a Resilient Supply Chain The manufacturing facilities in Europe are mostly fully automated with minimum touch on pallets from production all the way up to the docks but the last mile of action, i.e. loading operation remains fully manual with no flexibility to decide on how to execute this task (automated or manual). This makes it a weak link in the supply chain, which is prone to disruption (especially as learnt in COVID pandemic situation) as it is fully dependent on human presence to execute a labor intensive and less ergonomic task. Hence true supply chain resilience cannot be achieved until there is a solution developed to automatically load palletized goods with on the road (un-modified) European trailers. The main reason why this task is still conducted manually is the non-standard trailer fleet in Europe and the lack of no automatic solution available for curtain trailers. Given that curtain trailers comprise at least 80% of on the road trailers there is a huge opportunity with high scalability for a solution. However, currently existing solutions for automatic loading of pallets only work for loading rigid-walled trucks, which are characterized by rigid, nondeformed walls. In contrast, for loading of curtain trailers, such systems fail due to the varying conditions of curtain trailers and less defined walls resulting in these systems to crash into obstacles like carrier beams causing damaged loads or resulting in emergency stops. Consequently, this activity aims to enable an existing automatic loading solution (Nalon) of the company Duro Felguera to tackle the challenges associated with automatically loading curtain trailers from the rear side. Contact persons: L. Rolfs (Project manager)D. Niermann B. Vur Funded by: EU - EIT Manufacturing Duration: 01.01.2022 - 31.12.2022 See project's publications See project's page |
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Lernfabrik Energieautarke Produktion Die Lernfabrik vermittelt Studierenden auf Grundlage des didaktischen Konzeptes des forschenden und handlungsorientierten Lernens die Entwicklung energieautarker Produktionssysteme. Die Lernfabrik adressiert sowohl Lernziele der Produktionsplanung und -steuerung als auch der erneuerbaren Energieerzeugung, -speicherung und -nutzung. Studierende fertigen dabei reale Produkte, die in gesellschaftlichen und/ oder industriellen Anwendungen eingesetzt werden. Contact persons: M. Burwinkel (Project manager)Funded by: BREDE-Stiftung Duration: 01.12.2021 - 31.10.2022 See project's publications See project's page |
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EisAuge Ice detection on wind turbines using AI-assisted image processing Icing on rotor blades of wind turbines leads to downtimes every year and thus to considerable financial losses. The "EisAuge" project aims to develop a camera-based ice detection system to reduce these downtimes. The captured RGB and infrared images are analyzed by modern artificial intelligence (AI) methods to determine the current icing condition on the turbine rotor blades. The captured images and the model outputs are then stored in a cloud solution. BIBA is developing the camera system in this project. The goal here is a camera system that can capture sharp, detailed images both during the day and at night. In addition, BIBA is supporting the development of the AI algorithms in the project. For this purpose, modern methods of image processing, like for example Convolutional Neural Networks (CNNs), are utilized. The focus here is in particular on the transferability of the models to new wind turbines. Translated with www.DeepL.com/Translator (free version) Contact persons: M. Kreutz (Project manager)Funded by: Land Bremen / EFRE Duration: 16.07.2021 - 31.03.2023 See project's publications See project's page |
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DroneStock Unmanned aerial system for inventory recording and quality inspection of pallet contents in indoor block warehouses In this project we develop an unmanned aerial system (UAS) for automatic inventory recording and quality inspection of pallet contents in indoor block warehouses. The UAS should be able navigate autonomously through the block warehouse without the need for separation from humans or other autonomous systems. Calculations that require large computational effort, like e.g. image processing, are shifted to a mobile server, which is positioned inside the warehouse and comes with its own Wi-Fi network. This enables the use of more cost-effective drones and improves the scalability of the system. Contact persons: J. Arango Castellanos B. Staar Funded by: BMWi Duration: 01.07.2021 - 30.06.2023 See project's publications See project's page |
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Astradis Automated Specification Tool for AGV Deployment in SMBs In this research project, a tool is being developed to support the introduction of automated guided vehicles (AGVs). This includes a guided process and requirements analysis, in which the relevant data is determined and automatically compiled in a formated document for quotation requests. In addition, a manufacturer-independent catalog of AGVs available on the market is created, which can be automatically compared with the determined requirements in order to suggest suitable solutions to the user. Finally, the selection can be validated through the connection to a material flow simulation. Contact persons: N. Hoppe (Project manager)C. Petzoldt L. Rolfs Funded by: Land Bremen / EFRE Duration: 15.06.2021 - 30.09.2022 See project's publications See project's page (https://www.efre-bremen.de/) |
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PassForM Resource-based process management through flexible use of intelligent modules in hybrid assembly The PassForM research project creates a modularly reconfigurable assembly station. It allows for a more flexible design of manual and hybrid assembly stations and systematic automation, which improves scalability, re-usability and responsiveness to market developments. Bidirectional information and control instruction exchange enable and ease the integration of the modular assembly stations into existing assembly organizations. For this purpose, a material supply module, a conveyor module and a robot module are implemented. The goal is to unite the opposing requirements of productivity and flexibility in the assembly area of medium quantities. The project will fill the gap between manual and highly automated processes. The performance of the modular, hybrid assembly system will be evaluated and based on application scenarios in variant assembly groups. Contact persons: J. Wilhelm (Project manager)N. Hoppe Funded by: BMWi / AiF Duration: 01.06.2021 - 31.05.2023 See project's publications See project's page (passform.biba.uni-bremen.de) |
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Baeckerei 4.0 Development of a raw material-specific and cross-process production control in medium-sized bakeries using artificial intelligence The production of bakery products poses great challenges to process control in order to achieve consistent end product quality, as the main components of the products are natural products. The properties of the natural products strongly depend on the parameters during the growth and harvesting of the raw materials as well as their preliminary processes. The production of baked goods involves the product-specific combination of ingredients and the mechanical production of a dough, which is mostly kneaded. Low quality is often the result of incorrect expert assessment of raw material quality and the selected process parameters. A particular problem here is the process transitions or transfers between the process steps of dough preparation, work-up, fermentation phase, pre-baking phase, intermediate storage and post-baking phase. The aim of the project is to increase the product quality of baked goods. This should be achieved by developing a raw material-specific and cross-process production control system that uses artificial intelligence to improve coordination of the production processes while taking into account the specific parameters of the semi-finished products. The improved coordination of the production processes allows the reduction of rejects (resource conservation and traceability) as well as the planning/calculation of achievable product qualities based on quality raw material models to increase the specific process quality. Contact persons: A. Ait Alla (Project manager)Funded by: BMWi Duration: 01.06.2021 - 31.05.2023 See project's publications See project's page |
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Refine Tower Structure for Future Wind Energy Converters – Aeroelastic analysis, in-situ measurements and economic assessment of wind turbine tower structures According to the German Federal Environment Agency, wind energy is a cornerstone of the energy revolution. With increasing size, the efficiency but also the engineering challenges of modern wind turbines increase. One of these is the control of tower vibrations, which can, e.g., hinder erection or maintenance or lead to structural damage. The aim of the joint research project REFINE is to improve the understanding of the characteristics and causes of tower vibrations. Based on this, aerodynamic devices for towers will be developed and evaluated both technically and economically. For this purpose, a four-step approach will be followed: (1) With the help of innovative measurement technology developed at the University of Bremen, measurements will be carried out on a large fleet of onshore wind turbines over a longer period of time. (2) In addition, fluid mechanical simulations will be coupled with structural models of the wind turbines. (3) Based on this, aerodynamic devices to reduce vibration excitation will be developed and tested under real conditions. (4) The economic effects of the aerodynamic devices will be evaluated via holistic economic simulations. This research and development project is funded by the German Federal Ministry for Economic Affairs and Energy (German: Bundesministerium für Wirtschaft und Energie, BMWi) as part of “7th Energy Research Programme of the Federal Government”. Contact persons: S. Eberlein (Project manager)S. Oelker Funded by: BMWi Duration: 01.06.2021 - 31.05.2024 See project's publications See project's page (http://refine.science) |
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XCeedFeed Platform for optimized, automated, and intelligent processes to order and distribute compound-feed and for the re-supply of silos Agriculture must increasingly address issues of sustainability and quality management. In this context, feed is also becoming increasingly important from a cost perspective. The goal of the project is the realization of a cloud platform for farmers, traders, and feed producers to individually configure feed, produce it according to demand and deliver it just-in-time. In addition to the integration of weather-dependent demand and price forecasts, the focus is on the development of a simulation-based supply chain control with optimization of the life cycle assessment. Contact persons: D. Rippel (Project manager)Funded by: BMWK Duration: 01.06.2021 - 31.05.2023 See project's publications See project's page |
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DFWind_2 German Research Platform for Wind Energy - Phase 2 The primary objective of the project is to answer research questions to promote the expansion of wind energy against the background of economic efficiency and public acceptance, and to address questions relating to wind turbines that were previously impossible or difficult to answer. In setting up the wind energy research and development platform, the focus is on a holistic approach, in which the research focus is on the interaction of the subsystems in the overall wind turbine system, also taking into account the mutual influence of two separate wind turbines on each other. The University of Bremen will work on the instrumentation of the bearings with sensors and make preparations for data evaluation. In particular, the main bearing, the azimuth bearing, and the three blade flange bearings will be considered. Contact persons: S. Oelker (Project manager)Funded by: BMWi Duration: 01.12.2020 - 30.11.2023 See project's publications See project's page |
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MeshTrack Development of a hybrid RTT-/BLE positioning system for efficient asset tracking via mesh-based Beaconing The aim of this project is the development of a cost-efficient and easily deployable indoor positioning system. In contrast to existing approaches a hybrid approach is pursued: Established protocols like Bluetooth Low Energy (BLE) and WiFi RTT (round-trip-time) are combined into a mobile hybrid device. A key factor for deploying BLE-based indoor localization inside shop floors, is the utilization of a mesh network, whereby the BLE-Beacons are also connected to each other. This way the range of the BLE signal can be significantly improved, opening the possibility to cover large areas present in shop floors. Furthermore the project aims to implement real-time approaches for data retention on edge-computing platforms with intuitive user interfaces for industrial use. Contact persons: K. Klein B. Staar Funded by: BMWi Duration: 01.11.2020 - 31.10.2022 See project's publications See project's page |
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ViProQAS Visual Product Quality Auditing System ViProQAS addresses a system solution that enables the operative execution of quality inspection processes by means of visual support. For this purpose, the project is rethinking the way of visualization in the sense that the representation should take place through projections on 2D and 3D objects. App-based approaches with video and AR on mobile devices (glasses or tablets), as well as approaches based on virtual reality (VR) are deliberately not pursued, since the project not only aims at visualization, but also at recording and controlling the activities. This is not possible to a sufficient extent with the hardware currently available on the market. In the project, a framework is developed which derives the information for the assistance system from the audit specifications and subsequently forwards the recorded data to the corresponding systems. The innovation here is both the focus on the area of quality processes and the connection of visualization and recording as well as the control and documentation of the processes. Contact persons: D. Schweers (Project manager)A. Börold Funded by: BMWK Duration: 01.10.2020 - 30.09.2022 See project's publications See project's page |
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QualifyAR Development of an AR framework with extended sensor technology to support training and education in the aviation industry The project “QualifyAR” is to saims Accordingly, the use of digital and individual learning environments is pursued, intended to improve learning success and prepare the later use of digital assistance systems in the productive process. In cooperation with Radisumedia GmbH, an AR-based learning environment with context-sensitive information provision and automated learning success and quality testing is being developed. Using an AR framework and predefined process databases, teachers should be able to map teaching tasks independently digitally. Contact persons: R. Leder (Project manager)N. Jathe A. Rohde Funded by: BMWK Duration: 01.07.2020 - 30.04.2023 See project's publications See project's page |
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compARe Optimization of the maintenance of wind turbines by using image processing methods on mobile augmented reality devices In the funded project "compARe", an AR-based technical assistance system is developed that uses image processing methods to support service technicians in the maintenance of wind turbines. The project will focus on tasks that only allow defect detection by comparing the current status with a previously documented status or a target status. Thus, the system can help avoid damage to the WTG and increase maintenance measures' efficiency. Employing AI-based image processing methods, such as Convolutional Neural Networks (CNN), defects in components can be detected, classified, and evaluated. Furthermore, the comparison of component states based on historical data is possible. Mobile assistance systems have proven to be very promising for the support of service technicians in wind energy. The use of these computing-intensive image processing methods on mobile devices is a challenge. However, it offers great potential in combination with mobile Augmented Reality (AR) technology. In this way, virtual information on the change of component conditions can be provided directly about the components concerned in the field of vision of the service technicians. Contact persons: M. Quandt (Project manager)R. Leder W. Zeitler Funded by: BMWK Duration: 01.07.2020 - 30.06.2023 See project's publications See project's page |
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Isabella2.0 Automobile logistics in sea and inland ports: Integrated and user-oriented control of device and load movements through artificial intelligence and a virtual training application ** Motivation ** The results from Isabella generate first improvements of the initial situation and show further starting points for additional improvement. Our motivation is to take up these points and further improve the logistic performance of the control algorithm and to optimize it according to the specific situations. Moreover, an extension of the applicability of the control algorithm to the transhipment processes at different transport modes offers great potential to further improve the overall performance. In addition, it must not be ignored that the introduction of the solution approaches will be accompanied by radical changes in the work situations for the employees. Therefore, we are furthermore motivated to integrate the employees into the development of the new solutions such that overall we gain better acceptance of the final solution. **Objective** The aim is to optimize the parameterization of the control algorithm and to extend the approach regarding multi-criteria optimization so that the optimization performance can be further improved taking into account the prevailing situation such as terminal filling level, vehicle mix, personnel availability, etc. A further goal is the systematic extension of the control algorithm to the processes for loading and unloading the modes of transport (ship, train and truck) and the creation of a virtual training application. It will take up the psychological aspects regarding work and organization that result from the process redesigns, facilitate the changeover for the employees and finally ensure the acceptance of the new solution. ** Approach ** By means of event-discrete simulation, we will investigate the performance of the control algorithm under different environmental conditions and parameter settings. To this end we will use methods of sensitivity analysis and artificial intelligence and aim to draw conclusions between performance, terminal situation and parameter settings. As a result, it will be possible to adjust the control algorithm to the respective terminal situation and to increase the predictability of the operative processes. In addition, new data analysis methods and artificial intelligence approaches will be applied to systematically derive relevant process parameters from operationally acquired data, such as the duration of individual process steps or track utilisation. For the extension of the applicability of the control system to the modes of transport (train, ship, truck), a concept for data reception in ships and railway wagons will be designed. To this end, we will consider ad-hoc and mesh networks in combination with suitable radio standards such as WLAN, Bluetooth or LoRa. Contact persons: M. Hoff-Hoffmeyer-Zlotnik (Project manager)A. Ait Alla T. Sprodowski Funded by: BMVI Duration: 01.07.2020 - 30.06.2023 See project's publications See project's page |
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INSERT AI-based assistance system for concept planning in production and logistics Intense global competition, shorter product life cycles, and an increasing number of variants require flexible and adaptable, but also economical production and logistics systems. The time-intensive planning process shall be significantly shortened by an assistance system to become faster and more cost-efficient. In the project "INSERT", a prototype of an AI-based assistance system for concept development for logistics and production planning is being developed. This assistance system supports the entire planning process and provides a platform for the development of logistics and production concepts. Contact persons: L. Steinbacher M. Veigt Funded by: Land Bremen / EFRE Duration: 15.05.2020 - 30.11.2022 See project's publications See project's page |
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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 Manufacturing’s 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 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/) |
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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 today’s 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: J. Uhlenkamp A. Ait Alla S. Oelker A. Sander M. Stietencron Funded by: EU Duration: 01.05.2018 - 31.01.2026 See project's publications See project's page (realcoe.eu) |
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Mittelstand 4.0 Mid- & Small-Sized Enterprises Competency Center Bremen The Mittelstand 4.0-Kompetenzzentrum Bremen offers support to small and medium-sized enterprises in the Bremen region and surrounding areas, in increasing their digitalization competencies. In particular, employees and managers in the innovation clusters of maritime industry and logistics, wind energy, aerospace, automotive industry, and food and beverage industry are targeted. The competence center provides interested companies with a range of free services, according to their needs. The entire innovation process is covered, beginning with the assessment of a companyÂ’s digitalization potentials, and continuing with the opportunity to experience applications in practice. In parallel companies are given the opportunity to prepare themselves and their employees for the digital world through trainings. If desired, the center also accompanies companies in the implementation of their digital projects to ensure success. Contact persons: S. Wiesner (Project manager)H. Ekwaro-Osire A. Heuermann A. Himstedt M. Knak B. Knoke A. Seelig M. Teucke Funded by: BMWi Duration: 01.01.2018 - 31.12.2022 See project's publications See project's page (https://kompetenzzentrum-bremen.digital/) |
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CBS Improvement of Logistics Performance with Cluster-based Decentralized Control in Material Flow Networks The concept of decentrally controlled production and logistic systems has gained a growing importance as part of Industry 4.0. The previous research activities in this area focused mainly on the development of control algorithms for decision-making and the required information and communication technologies. An additional success factor for decentralized control has also been identified: the topology, i.e. the underlying structure of the material flow network. However, the topology has so far not been considered when developing decentralized control approaches. The project aims at quantifying the influence of the topology of a material flow network on the logistic performance. Furthermore, it is aspired to investigate how control algorithms need to be configured depending on the network structure. Contact persons: S. Schukraft D. Wagner-Kampik Funded by: DFG Duration: 16.08.2017 - 15.11.2022 See project's publications See project's page |
