Projects

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:
H. Ekwaro-Osire 
A. Himstedt 
M. Knak 
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)

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:
A. Rohde 
M. Trapp 

Funded by:
Land Bremen / EFRE / PFAU

Duration:
01.04.2023 - 31.05.2025

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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

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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)

M. Veigt 

Funded by:
EU - EIT Manufacturing

Duration:
01.01.2023 - 31.12.2024

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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

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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)


Funded by:
EU

Duration:
01.12.2022 - 31.05.2026

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See project's page (https://raresquare.eu/)

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

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See project's page

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 - 31.08.2024

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See project's page (https://ar-improve.biba.uni-bremen.de/)

Freight transport in Germany today is mainly carried out by road and rail. However, the further increase in transport volumes is pushing the systems to their limits, as evidenced by increased congestion and more frequent delivery delays, among other things. Another challenge is the high environmental impact of road and rail transport. A lower-emission alternative and supplement to land-based transport is water-based freight transport by inland waterway vessel. The increased use of this mode of transportation requires the provision of additional decentralized transhipment points (so-called MicroPorts) for the intelligent and efficient linking of land- and water-based freight transport. The aim of the project is the technical design of a network of decentralized transhipment hubs for linking land- and waterborne freight transport. The basic idea is to use existing infrastructure, especially bridges, for the installation of the MicroPorts. Based on this, a simulation-based evaluation will be carried out to assess the new transhipment concept's economic efficiency and sustainability. The expected project results thus provide the basis for the planning and implementation of decentralized transhipment points for combined land- and water-based freight transport in the future.

Contact persons:
S. Schukraft  (Project manager)

R. Leder 
B. Pupkes 
M. Trapp 

Funded by:
BMDV

Duration:
01.07.2022 - 30.06.2024

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See project's page

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

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See project's page

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

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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/)

This project aims at reducing technological barriers towards using a fleet of robots in warehouses and conventional manufacturing environments. In this project, learning material was created 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 the end-user perspective, our education materials helped 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 fully understanding the effect of underlying hyperparameters. In the second phase, the project will be expanded to include collaboration with manipulators to implement an efficient interface based on ROS2 components using the e.DO Cube from COMAU as an example. Based on this example, additional learning units related to ROS2 will be created to establish a fully comprehensive intralogistics scenario.

Contact persons:
T. Sprodowski  (Project manager)

S. Leohold 

Funded by:
EU - EIT Manufacturing

Duration:
01.01.2022 - 31.12.2023

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See project's page (http://imr.ciirc.cvut.cz/riemann/)

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:
B. Staar 

Funded by:
BMWi

Duration:
01.07.2021 - 30.06.2023

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See project's page

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)

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)

M. Lütjen 

Funded by:
BMWK

Duration:
01.06.2021 - 30.11.2023

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See project's page

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)

S. Leohold 

Funded by:
BMWi

Duration:
01.12.2020 - 30.11.2023

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See project's page

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 
H. Stern 
W. Zeitler 

Funded by:
BMWK

Duration:
01.07.2020 - 30.06.2023

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See project's page

** 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

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See project's page

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

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See project's page (https://eitmanufacturing.eu/)

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 

Funded by:
EU

Duration:
01.05.2018 - 31.01.2026

See project's publications
See project's page (realcoe.eu)