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.

In Port2Connect (Intelligent Port Logbook for the Efficient and Sustainable Use of Port Infrastructure), a digital port logbook is being developed that increases the transparency and visibility of processes in the port and enables automatic planning and optimisation with artificial intelligence.

processes in the port and enables automatic planning and optimisation with artificial intelligence. Through the intelligent monitoring and assistance system, ships are digitally accompanied and monitored during their stay in the port. In particular, this is intended to achieve the goals for more efficient use as well as sustainable protection against damage to the existing port infrastructure and an improvement in the climate by reducing emissions.

The port logbook is being developed as an example for 2,200 metres of the Stromkaje in Bremerhaven. Various requirements are placed on such a system. These include the recording and allocation of emissions as well as the location of the berths directly on the Weser, which are exposed to the river current and the tidal range caused by the tides. Furthermore, in order to use the berths efficiently, ships in the port must be moved more frequently. In addition, large container ships in particular pose an increased risk of damage to the infrastructure, and it is precisely these ships that account for a large proportion of the port’s total emissions.

In the SYDITIL project, a systemic digital twin (DT) for logistics is being developed. The technological basis is Σ, 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.

Stress and scarce attention are the main causes of work accidents in industry, and they affect workers' performance. Physical, physiological, and psychological aspects related to stress have already been studied through the analysis of biometric data, but they have never been integrated with neuro-physiological/psychological data. No-Stress captures the motion of workers while performing manufacturing tasks by real-time collecting neurophysiological parameters and interacting with voice assistance to gather reactions and feedback. The causes of stress will be identified by analyses of workers' data to redesign the work environment with a human-centred approach focused on worker well-being. The project will develop a monitoring system for manufacturing companies to improve their working conditions and production efficiency. The use case providers with worker assistance sector operators will work to redesign manufacturing contexts focusing on workers.

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.