Development of autonomous driving processes and dynamic storage and logistics concepts on automotive terminals
Duration 01.01.2024 - 31.12.2026, Funded by BMDV
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.
- M. Hoff-Hoffmeyer-Zlotnik () (Project manager)
Mensch-Technik-Interaktion, Prozessoptimierung und -steuerung, Maritime Wirtschaft, Automotive, Prozessmodellierung und Simulation, Drahtlose Kommunikationstechnologien und Sensorik
Development of a health-promoting assembly workplace with adaptive material provision and individual ergonomic optimization
01.09.2023 - 31.08.2025,
Funded by BMWK
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.
- R. Leder () (Project manager)
Mensch-Technik-Interaktion, Prozessoptimierung und -steuerung, Produzierendes Gewerbe, Digitaler Zwilling
Detection and AI-based analysis of ergonomic data in manual assembly using wearbles and machine vision techniques
Duration 01.09.2023 - 30.04.2025, Funded by Land Bremen
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.
- B. Vur () (Project manager)
- D. Schweers ()
Mensch-Technik-Interaktion, Produzierendes Gewerbe, Maschinelles Lernen / Künstliche Intelligenz, Training & Qualifizierung
Development of AR-based teleservices and intelligent job scheduling using diagnostic condition monitoring for the efficient maintenance of decentralized wastewater treatment plants
01.09.2023 - 31.08.2025,
Funded by BMWK / AiF
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.
- D. Rippel () (Project manager)
Produkt- und Prozessentwicklung, Digitalisierung, Energie und Umwelt, Dienstleistungen, Assistenzsysteme, Digitale Plattformen / IoT
Digitization of gluing processes in the automotive industry
01.08.2023 - 31.07.2026,
Funded by BMWK
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.
Digitalisierung, Prozessoptimierung und -steuerung, Automotive, Prozessmodellierung und Simulation, Maschinelles Lernen / Künstliche Intelligenz