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MobiTrans
Concept for a Mobile Transfer Unit (Living Hub)
Duration 01.06.2025 - 28.02.2026, Funded by BMBF
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In this project, a mobile transfer unit, the so-called "Living Hub," is conceptualized and precisely defined. The goal is to present existing knowledge as well as new insights gained from future community projects on Smartport topics in an engaging manner—such as through exhibits, demonstrators, prototypes, and simulations—and to make them accessible and usable both for the Smartport community and for the interested public, universities, and schools.
Contact person
- M. Lütjen () (Project manager)
Keywords
Value creation networks, Maritime economy, Knowledge transfer
MeisterWaerme
AI Assistance System for the Plumbing-Heating-Air-Conditioning (SHK) Trade to boost Process and Workforce E ciency through Knowledge-Based Maintenance of Thermal-Technology Systems
Duration
01.05.2025 - 30.04.2028,
Funded by BMWK / IGF
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The project’s centerpiece is an AI assistance system for the plumbing, heating and air-conditioning (SHK) trade that boosts process and workforce efficiency through knowledge-based maintenance of thermal-technology systems (e.g., heat pumps). By markedly improving first-time fault diagnosis and automating both repair and job preparation, the system aims to cut unproductive initial inspections and failed repair attempts—such as those caused by missing spare parts. To achieve this, plant data, maintenance documents (work reports, inspection protocols, maintenance checklists, etc.) and available remote-maintenance and smart-metering data are analyzed across companies and vendors using platform technologies, then transformed into knowledge representations for the AI assistant.
The BIBA as part of the project focuses on developing a semantic mediator middleware for data acquisition and transformation. In addition, a probabilistic workforce-scheduling module will be implemented to enable more efficient resource allocation within companies.
Contact person
- R. Hellbach () (Project manager)
Keywords
Digitalisation, Energy and environment, Construction industry, Process modelling and simulation, Semantic modelling and ontologies
SAILEX
Sales and operations intelligence with explainable AI
Duration
15.02.2025 - 15.08.2026,
Funded by Land Bremen / FEI
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The project aims to develop an AI-based analysis tool for ERP systems that combines sales data with internal and external factors. This will not only enable general sales trends to be recognised, but also individual correlations, such as discounts or external influences such as weather and political events. This helps to create more precise purchasing forecasts, avoid bottlenecks and reduce excess stock and reduce excess stock, which saves storage costs. In addition, a large language model is also used to explain the AI forecasts in order to ensure the traceability decisions, supported by explainable AI approaches.
Contact person
- S. Leohold () (Project manager)
Keywords
Digitalisation, Sustainability, Services industry, Trade and commerce, Assistance systems, Machine learning / artificial intelligence
Prophecy
Prognostic Model Selection for Predictive Maintenance and an Integrated Reinforcement Learning-based Production Scheduling in Dynamic Manufacturing Systems
Duration
01.02.2025 - 31.01.2027,
Funded by DFG
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This research project is a collaboration between the Bremer Institut für Produktion und Logistik (BIBA) at the University of Bremen, Germany, the Federal University of Rio Grande do Sul (UFRGS), Brazil, the Federal University of Santa Catarina (UFSC), Brazil, and the Federal University of Amazonas (UFAM), Brazil.
The goal of this project is to develop a self-adaptive model selection method for predictive maintenance that is fully integrated into production and maintenance planning. To achieve this, a machine learning-based approach will be developed, enabling the automated selection of suitable prognostic models for different system configurations and conditions. A key aspect is the incorporation of reinforcement learning for the dynamic optimization of machine availability and utilization in real time. This is based on a digital representation of the production system, which allows for the evaluation of decision impacts using production logistics KPIs. This performance assessment enables targeted feedback between meta-learning and reinforcement learning, contributing to the continuous improvement of the system.
A key aspect of the project is the integration of reinforcement learning to dynamically optimize machine availability and utilization in real time. This is based on a digital representation of the production system, allowing the assessment of decision impacts using production logistics KPIs. The continuous feedback loop between meta-learning and reinforcement learning facilitates the ongoing improvement of the system. To validate the developed methods, a simulation-based environment will be created, which replicates the relevant production and maintenance processes with the required level of abstraction. Finally, the developed system will be tested in two industrial use cases in Germany and Brazil.
Contact persons
- H. Engbers () (Project manager)
Keywords
System development and planning, Process optimisation and control, Automotive, Process modelling and simulation, Machine learning / artificial intelligence
Smartport Living Lab
Reactive, intelligent condition monitoring of the harbour superstructure
Duration
29.01.2025 - 31.12.2028,
Funded by Land Bremen / EFRE / EFRE-Bremen 2021 - 2027 (FKZ: 265/PF_BIBA_SMARTPORT/2025)
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The ‘Smartport Living Lab’ project addresses the challenges facing Bremen's ports in competition with the North Range ports. The aim is to develop innovative systems for a connected and sustainable port industry in Bremen/Bremerhaven. Flying drones and autonomous mobile robots are key technologies at BIBA for innovative condition monitoring solutions. These technologies are developed and tested in decentralised living labs, supported by a Smart Cooperation Platform that promotes collaboration between the participating research institutions and partners. The project strengthens the sustainable competitiveness and growth potential of the port locations and represents Bremen's innovative strength in maritime logistics.
Contact persons
- L. Rolfs () (Project manager)
- D. Keiser ()
- M. Kreutz ()
- C. Petzoldt ()
Keywords
Robotics and automation, Digitalisation, Maritime economy, Transport and logistics, Autonomous robot and transport systems, Machine learning / artificial intelligence
Events:
August 27, 2025, Friesland
“Green” Accents at the EnvoConnect 2025
September 3-4, 2025, Bremen
How Can Production and Logistics Be Truly “Green”?
September 8, 2025, BIBA, Bremen
KEDi Roadshow Bremen
September 9-10, 2025, Bremen
Artificial Intelligence as a Competitive Advantage for Your Company
September 11, 2025, BIBA, Bremen
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