Suction excavators are mainly used in areas where smaller building structures need to be exposed very precisely. For example, a defective gate valve of a water supply pipe that runs under a sidewalk needs to be replaced. Here, it is important to ensure that gas, telephone or power lines are not damaged by the suction process and that people in the vicinity of the suction vehicle are not harmed. In order to automate such a digging process, it is essential to recognize the situation in addition to precisely controlling the vacuum cleaner and planning and executing certain paths. As part of the doctoral project, innovative AI methods are to be investigated and applied to the suction excavator task on a test basis. The aim is to show whether it is possible to train a neural network based on image and distance data in such a way that the suction process is controlled directly by the network. Such a concept could be transferred to a large number of similar applications and would increase process quality while reducing costs at the same time.
Climate change brings with it many challenges, and wine and sparkling wine production is not unaffected. Extreme weather conditions affect the composition of the grapes and therefore also the fermentation process during wine and sparkling wine production. Small, family-run wineries in Rhineland-Palatinate, the backbone of the regional wine industry, face major challenges. In contrast to larger wineries, they often lack the technical and financial resources to adapt to the new conditions. The aim of this research project is to investigate how climate change affects the composition of grapes and how winegrowers can adapt their fermentation processes in order to continue producing high-quality wines and sparkling wines. This project not only secures the future of small wineries, but also contributes to the preservation of the cultural landscape and regional diversity in Rhineland-Palatinate. At the same time, it raises public awareness of the effects of climate change on viticulture.
Total final energy consumption in Germany is significantly influenced by heating and water heating in buildings. In 2022, the final energy consumption of private households amounted to 28.6 % of total energy consumption and is therefore higher than the consumption of the entire industrial sector. In order to achieve climate neutrality by 2045 as demanded by the German government, the energy consumption of buildings must be significantly reduced. This requires advanced energy supply systems that use renewable energies. As part of this research project, innovative thermo-electrical and electromechanical processes are being researched in order to supply buildings with energy in a highly efficient manner. In addition to researching the various energy supply methods, AI-supported computer systems are being used to investigate the optimization of overall building energy systems. The aim is to achieve a high level of energy efficiency and climate neutrality through a sensible combination of the respective thermoelectric and electromechanical systems
The aim of the research project is to find out how fasteners in timber-concrete composite construction behave when there is a fire. Wood-concrete composite construction is an innovative construction method that combines the advantages of wood and concrete to create load-bearing and sustainable buildings. In the event of a fire, the concrete is designed to prevent the wood from being exposed to the fire without protection. The fasteners are used to connect the two materials, concrete and wood.
The project aims to gather theoretical and practical information to improve the safety and performance of fasteners in timber-concrete construction in the event of fire. The results should contribute to the development of new and safer fastening options to enable a wider range of applications. The project will also contribute to the development of rules and standards for fire safety in timber construction.
The overarching aim of this project is to develop an ultra-slim concrete component. This can save resources and weight and thus protect the environment. As the most widely used building material in the world, concrete is indispensable, but causes high greenhouse gas emissions. Elsewhere, work is being carried out explicitly on the substitution of emission-causing substances. The approach of this project is to reduce the amount of concrete generally required by using effective methods. For example, high-strength concretes are selected that also require smaller quantities of material due to prestressing.
To transfer tensile forces in the concrete, it is necessary to incorporate steel, which requires minimum cover dimensions and thus "dead" material to protect against corrosion. In this project, the tensile forces are transferred via carbon tapes, which replace the integrated reinforcement in the concrete. This is the only way to achieve a significant reduction in material. Nevertheless, the findings from the development of the carbon tapes can also be applied elsewhere, for example in existing buildings.
The materials are analyzed and developed using computed tomography methods and photogrammetry. This allows the bonding behavior of the carbon tapes in particular to be precisely recorded.
In times of climate change and sustainability, the construction sector must also make its contribution. The amount of CO2 released during concrete production is the biggest challenge here, which is why research is being carried out into the use of alternative construction systems and materials. Due to its worldwide availability, ease of use and low energy requirements during processing, clay is an excellent building material for producing resource-saving and reusable components. For these reasons, RPTU is conducting research into walls made from rammed earth elements at its Kaiserslautern site. The aim of the research is to develop large-format wall elements that are easy to transport and enable simple assembly and disassembly. Dismantling and reuse eliminates the need to dispose of construction waste. Furthermore, earth is also much easier to recycle than concrete. All in all, earth building is therefore a sustainable alternative to concrete construction.
Autonomous robots that work independently have great potential, for example on construction sites, in agriculture or in disaster control. However, it has so far been difficult to network different machines with each other, especially if they come from different manufacturers. A key problem with the use of mixed robot systems is the lack of uniform standards: Machines from different manufacturers often do not speak the same "language", which makes direct collaboration difficult or impossible. This often leads to expensive adaptations and complex programming.
It is precisely these challenges that the project at RPTU is addressing. A so-called middleware is being developed, a technical mediation platform that functions like an interpreter between the machines. This middleware should not only ensure that robots can communicate with each other in a standardized way, but also that the exchanged data is correctly understood and interpreted. At the same time, work is being done to ensure that robots adapt dynamically to the situation at hand and flexibly change their tasks and behavior depending on what is needed in the overall system. It is particularly important that the system is suitable for practical use. This is why the technologies developed are tested in real scenarios, for example with autonomous construction vehicles on uneven terrain or in cooperative disaster control operations.
The aim is for these machines to be able to communicate directly with each other and carry out tasks together without the need for costly retrofitting each time. Initial tests will show how well the system works in realistic operational areas, for example on construction sites or in emergency situations. In the long term, the aim is to create a basis for new products and services from which small and medium-sized companies in the region in particular can benefit.
The research project aims to make industrial enzyme production more efficient through fungal fermentation. The focus is on optimizing processes with Aspergillus species for the production of important enzymes such as phytase, xylanase and cellulase.
To this end, an innovative approach is being pursued that combines biotechnological processes with artificial intelligence. With the help of data-based and knowledge-supported models, optimal process parameters are to be precisely predicted and fermentation processes controlled in real time. The aim is to achieve stable results across different reactor systems and to facilitate scaling up to larger production scales.
A particular focus is on the interaction between fungal morphology and enzyme production. By specifically controlling the process conditions, the aim is to achieve a form of fungal growth that enables maximum yields. After initial trials on a laboratory scale, the results will be transferred to larger plants.
In the long term, the project should contribute to making biotechnological production processes more economical, sustainable and efficient.
Additively manufactured components often have surfaces after production that are not yet sufficient for industrial use. The HybridAM project is developing processes that improve the quality and service life of components while at the same time conserving energy and resources. The focus is on components that are manufactured using high-speed laser deposition welding (HS DED-LB), a flexible and highly efficient process. For the post-processing of the components, various methods are combined into so-called hybrid process chains in order to make optimum use of their advantages. It is essential that the approaches can be implemented on conventional machine tools, which are already available in many small and medium-sized enterprises (SMEs). Based on the project results, a digital model will be created that enables the selection of the optimal process chain for different applications and can advance additive manufacturing in a technically, economically and ecologically sustainable manner.
The AURORA-6G project is developing innovative technologies to significantly increase productivity and flexibility in industrial production. The focus is on intelligent 6G networks, autonomous robots and a semantic framework that enables components to be integrated quickly and easily into existing systems.
The so-called AURORA framework creates the basis for new business models such as "as-a-service" concepts in production and intralogistics. Thanks to standardized, flexible interfaces and so-called "skills", robots can be controlled more efficiently, set up more quickly and, if necessary, monitored remotely.
The technological basis is 6G networking, which enables direct and powerful communication between machines, vehicles and robots. This is supplemented by edge computing to reduce the load on the systems and XR technologies that facilitate operation and monitoring. The connection to digital twins also supports the planning, simulation and optimization of production and logistics processes.
In Rhineland-Palatinate, the manufacturing industry plays a central role in employment and value creation. In the face of growing challenges such as global competitive pressure, rising costs and disrupted supply chains, innovations - particularly in the field of artificial intelligence (AI) - are crucial for competitiveness, especially for small and medium-sized enterprises (SMEs).
Despite its great potential, AI is still underutilized in industrial practice. The main reason for this is the gap between research and application, as many AI approaches are not designed for the complex conditions of real production data.
The aim is therefore to make AI research more practice-oriented: the development and testing of concrete applications in production, a targeted focus on the needs of SMEs and an accelerated transfer of knowledge and technology should help to transfer AI solutions into industrial practice more quickly and easily.
Small and medium-sized enterprises (SMEs) are faced with the challenge of making their production processes more efficient and flexible in the face of growing product diversity. The effort involved is particularly high in robot-assisted production, as product variants often still have to be programmed manually.
This is where the project comes in and aims to facilitate access to modern technologies such as artificial intelligence, collaborative robots and digital control systems. The aim is to optimize production processes in a semi-automated manner without displacing people from the center.
The core of the project is a model that gradually introduces companies to new automation solutions. Historical production data is used to make suggestions for process design, which are then adapted by specialists. This is supplemented by a flexible software infrastructure based on open standards, which enables simple integration of existing systems.
Close cooperation with industry partners is intended to create practical solutions that show SMEs concrete paths towards Digitalization and sustainable automation.